tag:blogger.com,1999:blog-85998511357906910752023-11-15T06:01:37.199-08:00Is Advanced Machine Learning an old wine in a new bottle?Anonymoushttp://www.blogger.com/profile/16651671191775875167noreply@blogger.comBlogger9125tag:blogger.com,1999:blog-8599851135790691075.post-72704610963114831532016-05-15T18:22:00.000-07:002016-05-15T18:22:20.406-07:00Response to the article: Three Trends That Will Define the Next Horizon in Legal Research by (FITZPATRICK, 2015).
<br />
<div class="MsoNormal" style="line-height: normal; margin: 0cm 0cm 10pt; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; mso-outline-level: 2; text-align: justify;">
<span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-font-family: "Times New Roman"; mso-fareast-language: EN-ZA; mso-themecolor: text1;">Response
to the article:</span><span style="font-family: "Arial","sans-serif"; font-size: 12pt;">
T</span><span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-font-family: "Times New Roman"; mso-fareast-language: EN-ZA; mso-themecolor: text1;">hree Trends That Will Define the Next Horizon in
Legal Research by <w:sdt citation="t" id="1490597928"><!--[if supportFields]><span
style='mso-element:field-begin'></span><span style='mso-spacerun:yes'> </span>CITATION
SEA15 \l 7177 <span style='mso-element:field-separator'></span><![endif]--><span style="mso-no-proof: yes;">(FITZPATRICK, 2015)</span><!--[if supportFields]><span
style='mso-element:field-end'></span><![endif]--></w:sdt>. In this article FitzPatrick
is talking about the quintillion of data created everyday by humans, the
decreasing storage space and the inability for people to handle this amount of
data. He discusses tools such as natural language and machine learning as being
able to assist professionals to bridge the gap of having big data and being
able to dissect it,<span style="mso-spacerun: yes;"> </span>he goes on to
describe a group of people who occupied work force after the year 2000 referring
to the as Millenials. His argument is that this group understand technology and
are comfortable to use it better than those who started working prior to
2000.<span style="mso-spacerun: yes;"> </span><o:p></o:p></span></div>
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<span style="font-family: "Arial","sans-serif"; font-size: 12pt;">Natural language,
machine learning and these Millenials is what he refers to as the three trends
that will define the new horizon in legal research. He argues that machine
learning will be able to help lawyers get accurate answers faster by learning
from the available databases and learning how users interact with data
adjusting their algorithms to be more accurate when similar situations occur.<o:p></o:p></span></div>
<br />
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<span style="font-family: "Arial","sans-serif"; font-size: 12pt;">I agree with </span><span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-font-family: "Times New Roman"; mso-fareast-language: EN-ZA; mso-themecolor: text1;">FitzPatrick
on the trends especially machine learning having the capability to improve how
data is manipulated. I also agree with him on these young employees that he
refers to as millennials, they happen not to be frightened by technology, like
exploring and inquisitive.<span style="mso-spacerun: yes;"> </span><o:p></o:p></span></div>
<br />
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<span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-font-family: "Times New Roman"; mso-fareast-language: EN-ZA; mso-themecolor: text1;"><w:sdt citation="t" id="1836263788"><!--[if supportFields]><span style='mso-element:
field-begin'></span><span style='mso-spacerun:yes'> </span>CITATION Yan16 \l
7177 <span style='mso-element:field-separator'></span><![endif]--><span style="mso-no-proof: yes;">(Yang, 2016)</span><!--[if supportFields]><span
style='mso-element:field-end'></span><![endif]--></w:sdt>Explains the use of
actuarial method of risk assessment that compares individual behaviour to a
norm-based reference group. He argues that “</span><span style="font-family: "Arial","sans-serif"; font-size: 12pt;">Since <span class="hithilite">machine learning</span>
algorithm can be very good at detecting hard to observe relationship between
data, it may be possible to detect obscured association between certain
variables in criminal case and particular <span class="hithilite">legal</span>
outcomes” the argument that agrees with the one for FitzPatrick.</span><span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-font-family: "Times New Roman"; mso-fareast-language: EN-ZA; mso-themecolor: text1;"><o:p></o:p></span></div>
<br />
<div class="MsoNormal" style="line-height: normal; margin: 0cm 0cm 10pt; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; mso-outline-level: 2; text-align: justify;">
<span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-font-family: "Times New Roman"; mso-fareast-language: EN-ZA; mso-themecolor: text1;">In
conclusion I agree with him these technologies will not only change the horizon
of legal research but of many industries that take advantage of them and big
data.<o:p></o:p></span></div>
<br />
<div class="MsoNormal" style="line-height: normal; margin: 0cm 0cm 10pt; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; mso-outline-level: 2; text-align: justify;">
<span style="color: black; font-family: "Arial","sans-serif"; font-size: 10pt; mso-fareast-font-family: "Times New Roman"; mso-fareast-language: EN-ZA; mso-themecolor: text1;">Referenes:<o:p></o:p></span></div>
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<w:sdt docparttype="Bibliographies" docpartunique="t" id="302433103" sdtdocpart="t">
<br />
<h1 style="margin: 24pt 0cm 0pt;">
<!--[if supportFields]><span lang=EN-US style='font-size:10.0pt;
line-height:115%;font-family:"Arial","sans-serif";font-weight:normal'><span
style='mso-element:field-begin'></span></span><span lang=EN-US
style='font-size:10.0pt;line-height:115%;font-family:"Arial","sans-serif"'><span
style='mso-spacerun:yes'> </span>BIBLIOGRAPHY </span><span lang=EN-US
style='font-size:10.0pt;line-height:115%;font-family:"Arial","sans-serif";
font-weight:normal'><span style='mso-element:field-separator'></span></span><![endif]--><span lang="EN-US" style="font-family: "Arial","sans-serif"; font-size: 10pt; line-height: 115%; mso-no-proof: yes;"><o:p></o:p></span><span lang="EN-US" style="font-family: "Arial","sans-serif"; font-size: 10pt; line-height: 115%;"><w:sdtpr></w:sdtpr></span></h1>
<br />
<div class="MsoBibliography" style="margin: 0cm 0cm 10pt 36pt; text-indent: -36pt;">
<span lang="EN-US" style="font-family: "Arial","sans-serif"; font-size: 10pt; line-height: 115%; mso-ansi-language: EN-US; mso-no-proof: yes;">FITZPATRICK, S. (2015). <i>Three
Trends That Will Define the Next Horizon in Legal Research.</i> Information
Today.<o:p></o:p></span></div>
<br />
<div class="MsoBibliography" style="margin: 0cm 0cm 10pt 36pt; text-indent: -36pt;">
<span lang="EN-US" style="font-family: "Arial","sans-serif"; font-size: 10pt; line-height: 115%; mso-ansi-language: EN-US; mso-no-proof: yes;">Yang, J. (2016). Digitalization of
the Criminal Justice Procedure and Applying Big data Analytics in
Rationalization of Criminal Sentencing. <i>Journal of hongik law review</i>,
419-448.<o:p></o:p></span></div>
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<!--[if supportFields]><b><span style='font-size:10.0pt;
line-height:115%;font-family:"Arial","sans-serif"'><span style='mso-element:
field-end'></span></span></b><![endif]--><o:p><span style="font-family: Calibri;"> </span></o:p></div>
</w:sdt><br />Anonymoushttp://www.blogger.com/profile/16651671191775875167noreply@blogger.com0tag:blogger.com,1999:blog-8599851135790691075.post-80599571085858095292016-05-15T17:07:00.002-07:002016-05-15T17:07:39.522-07:00A response on press release titled: Avik Partners Unfurls Machine Learning Service to Optimize IT Operations by Mike Vizard.<br />
<span style="font-family: Arial, Helvetica, sans-serif;"><div class="MsoNormal" style="line-height: normal; margin: 0cm 0cm 10pt; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; mso-outline-level: 2; text-align: justify;">
<span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-font-family: "Times New Roman"; mso-fareast-language: EN-ZA; mso-themecolor: text1;">In
this release posted on the 6 October 2015 on ITBusinessEdge Mike Vizard
announces the unveiling of Grok by Avik Partners. There are other press
releases by Chris Talbot and San Clemente on the same day on the same topic.</span><span style="color: black; font-family: "Times New Roman","serif"; font-size: 12pt; mso-fareast-font-family: "Times New Roman"; mso-fareast-language: EN-ZA; mso-themecolor: text1;"><o:p></o:p></span></div>
<div class="MsoNormal" style="line-height: normal; margin: 0cm 0cm 10pt; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; mso-outline-level: 2; text-align: justify;">
<span style="font-family: Times New Roman;">
</span><span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-font-family: "Times New Roman"; mso-fareast-language: EN-ZA; mso-themecolor: text1;">In
his release Vizard explain Grok as a "Saas application for managing IT environments that
first identifies optimal patterns in an IT environment to better identify
anomalies that adversely affect application performance and then, secondly,
continues to learn about the environment as new IT resources are added", he
however does not elaborate on how this is being achieved and who will be using
it. On the other hand Talbot and Clemente on their version explains that the
application has a combination of adaptive and automation to detect unusual
behaviour. They further explain that the application is for use by companies
that uses public or private cloud services. I think this information is
important for companies who will want to use this application; with less information
companies may be reluctant to adopt the application.</span><span style="color: black; font-family: "Times New Roman","serif"; font-size: 12pt; mso-fareast-font-family: "Times New Roman"; mso-fareast-language: EN-ZA; mso-themecolor: text1;"><o:p></o:p></span></div>
<div class="MsoNormal" style="line-height: normal; margin: 0cm 0cm 10pt; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; mso-outline-level: 2; text-align: justify;">
<span style="font-family: Times New Roman;">
</span><span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-font-family: "Times New Roman"; mso-fareast-language: EN-ZA; mso-themecolor: text1;">Another
point that Mike is not quoting from the CEO of Avik is that of using Saas
approach which both Talbot and Clemente are quoting. I find Mike’s release less
informative and hiding much information that could assist companies in making
decisions on whether to adopt Grok or not.</span><span style="color: black; font-family: "Times New Roman","serif"; font-size: 12pt; mso-fareast-font-family: "Times New Roman"; mso-fareast-language: EN-ZA; mso-themecolor: text1;"><o:p></o:p></span></div>
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<span style="font-family: Times New Roman;">
</span></div>
</span><div class="MsoNormal" style="line-height: normal; margin: 0cm 0cm 10pt; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; mso-outline-level: 2; text-align: justify;">
<span style="font-family: "Arial","sans-serif"; font-size: 12pt;">References:<o:p></o:p></span></div>
<span style="font-family: "Arial","sans-serif"; font-size: 12pt;">Mike Vizard, 06
October 2015, <a href="http://www.itbusinessedge.com/blogs/it-unmasked/avik-partners-unfurls-machine-learning-service-to-optimize-it-operations.html"><span style="color: blue;">http://www.itbusinessedge.com/blogs/it-unmasked/avik-partners-unfurls-machine-learning-service-to-optimize-it-operations.html</span></a><o:p></o:p></span><br />
<br />
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<span style="font-family: "Arial","sans-serif"; font-size: 12pt;">Chris Talbot, 06
October 2015, <a href="http://www.fiercedevops.com/story/avik-partners-emerges-grok-machine-learning-saas/2015-10-06"><span style="color: blue;">http://www.fiercedevops.com/story/avik-partners-emerges-grok-machine-learning-saas/2015-10-06</span></a><o:p></o:p></span></div>
<b><span style="color: #4e4e4e; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-font-family: "Times New Roman"; mso-fareast-language: EN-ZA; text-transform: uppercase;">San Clemente, Calif. (PRWEB) October 06, 2015 <a href="http://www.prweb.com/releases/2015/10/prweb13004074.htm"><span style="color: blue;">http://www.prweb.com/releases/2015/10/prweb13004074.htm</span></a><o:p></o:p></span></b><br />
<br />
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<b><span style="color: #4e4e4e; font-family: Roboto; font-size: 9pt; mso-bidi-font-family: Arial; mso-fareast-font-family: "Times New Roman"; mso-fareast-language: EN-ZA; text-transform: uppercase;"><o:p> </o:p></span></b></div>
Anonymoushttp://www.blogger.com/profile/16651671191775875167noreply@blogger.com0tag:blogger.com,1999:blog-8599851135790691075.post-18972164639996558132016-05-14T10:06:00.001-07:002016-05-14T10:06:55.523-07:00Machine Learning Tools and how Companies Leverage on Machine Learning Algorithms
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<a href="https://www.google.co.za/imgres?imgurl=http://www.aronsonsecurity.com/Portals/55833/images/Machine_Learning.jpg&imgrefurl=https://worldindustrialreporter.com/darpa-envisions-the-future-of-machine-learning/&docid=nv4ISMaOvSDsGM&tbnid=cH5bzNHfaL-T0M:&w=1280&h=720&bih=802&biw=1670&ved=0ahUKEwin8q7j89nMAhUrDcAKHXzIDHoQMwhHKCIwIg&iact=mrc&uact=8"><span style="color: blue; font-family: "Arial","sans-serif"; font-size: 13.5pt; mso-fareast-language: EN-ZA; mso-no-proof: yes; text-decoration: none; text-underline: none;"><!--[if gte vml 1]><v:shapetype
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<div class="MsoNormal" style="line-height: normal; margin: 0cm 0cm 10pt; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; mso-outline-level: 2; text-align: justify;">
<span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;">As with any
other technology we see companies taking advantage and building machine
learning tools that they avail for use either on the cloud or can be dowloaded
and used at your local machine.<o:p></o:p></span></div>
<br />
<div class="MsoNormal" style="line-height: normal; margin: 0cm 0cm 10pt; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; mso-outline-level: 2; text-align: justify;">
<span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;">At the for
front we see IBM with Watson that offer varried servises, Microsoft with Azure
and Predictive Analytics, Google with Google Translate and Google Prediction
API and Amazon with Predictive Analytics with Amazon Web Services.<o:p></o:p></span></div>
<br />
<div class="MsoNormal" style="line-height: normal; margin: 0cm 0cm 10pt; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; mso-outline-level: 2; text-align: justify;">
<span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;">There is also
a lots of startups and open source machine learning tools that are battling
their space with Loius Dorard mentioning PredicSis and BigML as providing a
competing API’s when compared with the top 4. Below is a list of some of the startups
and open source tools:<o:p></o:p></span></div>
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<span style="color: black; font-family: "Arial","sans-serif"; font-size: 10pt; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;"><a href="https://www.crunchbase.com/category/machinelearning/5ea0cdb7c9a647fc50f8c9b0fac04863"><span style="color: black; mso-themecolor: text1;">https://www.crunchbase.com/category/machinelearning/5ea0cdb7c9a647fc50f8c9b0fac04863</span></a><o:p></o:p></span></div>
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<span style="color: black; font-family: "Arial","sans-serif"; font-size: 10pt; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;"><a href="http://www.infoworld.com/article/2853707/machine-learning/11-open-source-tools-machine-learning.html#slide1"><span style="color: black; mso-themecolor: text1;">http://www.infoworld.com/article/2853707/machine-learning/11-open-source-tools-machine-learning.html#slide1</span></a><o:p></o:p></span></div>
<br />
<div class="MsoNormal" style="line-height: normal; margin: 0cm 0cm 10pt; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; mso-outline-level: 2; text-align: justify;">
<span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;">How then; can
companies leverage on this technology that is obviously gaining momentum. Daxx
mention 6 ways that companies are leveraging Machine Learning Algorithms as:<o:p></o:p></span></div>
<br />
<div class="MsoListParagraphCxSpFirst" style="line-height: normal; margin: 0cm 0cm 0pt 36pt; mso-add-space: auto; mso-list: l0 level1 lfo1; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; mso-outline-level: 2; text-align: justify; text-indent: -18pt;">
<!--[if !supportLists]--><span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-font-family: Arial; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;"><span style="mso-list: Ignore;">1.<span style="font-size-adjust: none; font-stretch: normal; font: 7pt/normal "Times New Roman";">
</span></span></span><!--[endif]--><span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;">Price
Optimization<o:p></o:p></span></div>
<br />
<div class="MsoListParagraphCxSpMiddle" style="line-height: normal; margin: 0cm 0cm 0pt 36pt; mso-add-space: auto; mso-list: l0 level1 lfo1; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; mso-outline-level: 2; text-align: justify; text-indent: -18pt;">
<!--[if !supportLists]--><span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-font-family: Arial; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;"><span style="mso-list: Ignore;">2.<span style="font-size-adjust: none; font-stretch: normal; font: 7pt/normal "Times New Roman";">
</span></span></span><!--[endif]--><span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;">Improving Customer
Engagement and Maximizing Profits<o:p></o:p></span></div>
<br />
<div class="MsoListParagraphCxSpMiddle" style="line-height: normal; margin: 0cm 0cm 0pt 36pt; mso-add-space: auto; mso-list: l0 level1 lfo1; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; mso-outline-level: 2; text-align: justify; text-indent: -18pt;">
<!--[if !supportLists]--><span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-font-family: Arial; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;"><span style="mso-list: Ignore;">3.<span style="font-size-adjust: none; font-stretch: normal; font: 7pt/normal "Times New Roman";">
</span></span></span><!--[endif]--><span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;">Launching
Targeted Promotions<o:p></o:p></span></div>
<br />
<div class="MsoListParagraphCxSpMiddle" style="line-height: normal; margin: 0cm 0cm 0pt 36pt; mso-add-space: auto; mso-list: l0 level1 lfo1; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; mso-outline-level: 2; text-align: justify; text-indent: -18pt;">
<!--[if !supportLists]--><span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-font-family: Arial; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;"><span style="mso-list: Ignore;">4.<span style="font-size-adjust: none; font-stretch: normal; font: 7pt/normal "Times New Roman";">
</span></span></span><!--[endif]--><span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;">Predicting
Equipment Failure<o:p></o:p></span></div>
<br />
<div class="MsoListParagraphCxSpMiddle" style="line-height: normal; margin: 0cm 0cm 0pt 36pt; mso-add-space: auto; mso-list: l0 level1 lfo1; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; mso-outline-level: 2; text-align: justify; text-indent: -18pt;">
<!--[if !supportLists]--><span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-font-family: Arial; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;"><span style="mso-list: Ignore;">5.<span style="font-size-adjust: none; font-stretch: normal; font: 7pt/normal "Times New Roman";">
</span></span></span><!--[endif]--><span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;">Detecting
and Preventing Fraud<o:p></o:p></span></div>
<br />
<div class="MsoListParagraphCxSpLast" style="line-height: normal; margin: 0cm 0cm 10pt 36pt; mso-add-space: auto; mso-list: l0 level1 lfo1; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; mso-outline-level: 2; text-align: justify; text-indent: -18pt;">
<!--[if !supportLists]--><span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-font-family: Arial; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;"><span style="mso-list: Ignore;">6.<span style="font-size-adjust: none; font-stretch: normal; font: 7pt/normal "Times New Roman";">
</span></span></span><!--[endif]--><span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;">Streamlining
Talent Acquisition<o:p></o:p></span></div>
<br />
<div class="MsoNormal" style="line-height: normal; margin: 0cm 0cm 10pt; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; mso-outline-level: 2; text-align: justify;">
<span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;">If your
organisation has not thought about how to use machine learning this is the
time.<o:p></o:p></span></div>
<br />
<div class="MsoNormal" style="line-height: normal; margin: 0cm 0cm 10pt; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; mso-outline-level: 2; text-align: justify;">
<span style="color: black; font-family: "Arial","sans-serif"; font-size: 10pt; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;"><span style="mso-spacerun: yes;"> </span></span><span style="color: black; font-family: "Arial","sans-serif"; font-size: 12pt; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;">References: <o:p></o:p></span></div>
<br />
<div class="MsoNormal" style="line-height: normal; margin: 0cm 0cm 10pt; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; mso-outline-level: 2; text-align: justify;">
<span style="color: black; font-family: "Arial","sans-serif"; font-size: 10pt; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;"><a href="http://machinelearningmastery.com/machine-learning-tools/"><span style="color: black; mso-themecolor: text1;">http://machinelearningmastery.com/machine-learning-tools/</span></a><o:p></o:p></span></div>
<br />
<div class="MsoNormal" style="line-height: normal; margin: 0cm 0cm 10pt; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; mso-outline-level: 2; text-align: justify;">
<span style="color: black; font-family: "Arial","sans-serif"; font-size: 10pt; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;"><a href="http://www.infoworld.com/article/2853707/machine-learning/11-open-source-tools-machine-learning.html#slide1"><span style="color: black; mso-themecolor: text1;">http://www.infoworld.com/article/2853707/machine-learning/11-open-source-tools-machine-learning.html#slide1</span></a><o:p></o:p></span></div>
<br />
<div class="MsoNormal" style="line-height: normal; margin: 0cm 0cm 10pt; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; mso-outline-level: 2; text-align: justify;">
<span style="color: black; font-family: "Arial","sans-serif"; font-size: 10pt; mso-fareast-language: EN-ZA; mso-no-proof: yes; mso-themecolor: text1;"><a href="http://www.daxx.com/article/machine-learning-insights-for-your-business"><span style="color: black; mso-themecolor: text1;">http://www.daxx.com/article/machine-learning-insights-for-your-business</span></a><o:p></o:p></span></div>
Anonymoushttp://www.blogger.com/profile/16651671191775875167noreply@blogger.com4tag:blogger.com,1999:blog-8599851135790691075.post-72893532119261133132016-05-11T04:34:00.000-07:002016-05-11T22:06:28.012-07:00An Interview with Bennie Leonard a Machine Learning Scientist at DataProphet - Special Post<div style="text-align: justify;">
DataProphet is a South African, Cape Town based Consulting company that specialises in Machine Learning. I have had an opportunity to ask some questions from Bennie Leonard who is a Machine Learning Scientist at DataProphet. <span style="font-family: "times new roman" , "serif"; font-size: 12pt;">Thank you Bennie for the
insights. </span></div>
<span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;"><strong></strong></span><div style="margin: 0cm 0cm 0pt; text-align: justify;">
<br /></div>
<span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;"><strong>
</strong></span><span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;"><strong><div style="margin: 0cm 0cm 0pt; text-align: justify;">
<br /></div>
</strong></span><br />
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;"><strong>Q</strong>. I see you are a Machine Learning Scientist at DataProphet. Where did
you study </span><span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;">machine learning?</span></div>
<div style="text-align: justify;">
<br /></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;"> </span><span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;"><strong>A</strong>. I studied computer science at the University of Pretoria. I
specialised in optimisation </span><span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;">algorithms, with a focus on swarm intelligence. Optimisation algorithms
are a class of </span><span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;">clever search methods and are often used to enable machines to learn
from experience.</span></div>
<div style="text-align: justify;">
<br /></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;"><strong>Q</strong>. Why did you choose machine learning as a career?</span></div>
<div style="text-align: justify;">
<br /></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;"> </span><span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;"><strong>A</strong>. Programming computers to learn has been a field of interest for
scientists for at least a few decades. However, over the last ten years or so,
the field has gained substantial traction in real-world applications. Machine
learning is widely used in the technology industry to perform a range of tasks,
including product suggestions in online shopping, search prediction for online
search engines, and even mastering difficult games like Go. </span><span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;">Even so, there are still a huge number of businesses that are either
unaware of the </span><span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;">capabilities and potential benefits of machine learning, or struggle to
understand how to apply machine learning to their unique business environments.</span></div>
<div style="text-align: justify;">
<br /></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;">The enormous potential that machine learning and artificial intelligence
has to offer, and the excitement of working in a very young and developing
field, are what drove me into a career focussed on machine learning. At
DataProphet we aim to understand and fill the gap between scientific advances
in machine learning and the useful application thereof to individual
businesses.</span></div>
<div style="text-align: justify;">
<br /></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;"><strong>Q</strong>. What algorithms do you apply on your job as a machine learning
specialist and why?</span></div>
<div style="text-align: justify;">
<br /></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;"><strong>A</strong>. Different applications of machine learning often require unique
combinations of </span><span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;">algorithms to perform a given task. Our expertise at DataProphet ranges
from relatively old (and commonly used) tree-based classification methods to
the most recent developments in deep neural networks. Which specific algorithms
to apply depends heavily on the scope and specifications of each individual
project.</span></div>
<div style="text-align: justify;">
<br /></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;"><strong> </strong></span><span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;"><strong>Q</strong>. We have professionals that are well known for their work in machine
learning, who do you look up to?</span></div>
<div style="text-align: justify;">
<br /></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;"><strong> </strong></span><span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;"><strong>A</strong>. There are many highly respected professionals in the field, but
progress rarely comes without relying on the work of other scientists.
Personally, I have deep admiration for the likes of Alan Turing, John von Neumann,
and Ada Lovelace, who played crucial roles in laying the foundations for the
science we build upon today.</span></div>
<div style="text-align: justify;">
<br /></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;"> </span><span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;"><strong>Q</strong>. What is the adoption rate of machine learning in South Africa?</span></div>
<div style="text-align: justify;">
<br /></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;"> </span><span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;"><strong>A</strong>. It’s hard to put a figure on the adoption rate of machine learning in
South Africa. While it is definitely increasing, we often find that businesses
are either overly optimistic, or overly skeptical when it comes to machine
learning. There is still a lot to do in terms of educating people as to what
the capabilities of machine learning are. With a better understanding of the
technology, the adoption rate will likely increase faster.</span></div>
<div style="text-align: justify;">
<br /></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;"><strong>Q</strong>. I had a presentation on machine learning where I gave an example of
(FITZPATRICK,</span><span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;">2015) article “Three Trends That Will De</span><span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-font-family: MS-Gothic; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;">fi</span><span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;">ne the Next Horizon in Legal Research”
where he talks about machine learning as one of the trends. The question that I
got was around ethical issues when training these models. What is your take on
that?</span></div>
<div style="text-align: justify;">
<br /></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;"><strong> </strong></span><span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;"><strong>A</strong>. As with any technology, it is important to consider the ethical implications.
</span><span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;">Machine learning models are trained on the data that humans provide them
with. In that sense, the algorithms are general-purpose algorithms. They will
attempt to understand any data that is presented to them and the trained models
can be applied in any way we wish to apply them. Throughout history (and still
today) there are many examples of technology being used in unethical ways. It
would be naive to think that machine learning is somehow immune to this
possibility. Indeed, companies like Google’s Deep Mind and the non-profit OpenAI
have already established ethics boards to guard against the unethical
application of artificial intelligence, and rightly so. </span></div>
<span style="font-family: "calibri";"></span><div style="margin: 0cm 0cm 0pt; text-align: justify;">
<br /></div>
<span style="font-family: "calibri";">
</span><br />
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;">However, the intent of
scientific research is ultimately to expand and enrich human knowledge. That
intelligence forms part of who we are is indisputable. And in our quest to truly
understand intelligence, we will undoubtedly learn more about ourselves. So we
are faced with two choices: we can either continue on this path to discover the
true nature of intelligence, while being mindful of the potentially far-reaching
ethical implications of what we might learn; or we can credulously decide that
the risk is too great and be willfully ignorant about this mysterious quality
we call intelligence, that is such a big part of who we are. We should all
choose the former.</span></div>
<div style="text-align: justify;">
<br /></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: "calibri" , "sans-serif"; mso-ascii-theme-font: minor-latin; mso-bidi-theme-font: minor-latin; mso-fareast-language: EN-US; mso-hansi-theme-font: minor-latin;">Bennie Leonard</span></div>
Anonymoushttp://www.blogger.com/profile/16651671191775875167noreply@blogger.com3tag:blogger.com,1999:blog-8599851135790691075.post-24250948415557047872016-05-09T07:52:00.000-07:002016-05-11T06:44:23.358-07:00Some Applications of Machine Learning<span style="font-family: "arial" , "helvetica" , sans-serif;"><span style="font-family: "arial" , "sans-serif"; line-height: 115%;"><span style="font-family: "arial" , "sans-serif";">In this section I will
discuss some machine learning algorithms and their application. Will
discuss supervised learning and unsupervised learning, active learning and
transfer learning.</span></span></span><br />
<div style="margin: 0cm 0cm 10pt;">
<span style="font-family: "arial" , "helvetica" , sans-serif;"><span style="font-family: "arial" , "sans-serif"; line-height: 115%;"><span style="font-family: "times new roman";">
</span></span></span><br />
<span style="font-family: "arial" , "helvetica" , sans-serif;"><span style="font-family: "arial" , "sans-serif"; line-height: 115%;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "arial" , "sans-serif";">Supervised learning</span></b></span></span><br />
<span style="font-family: "arial" , "helvetica" , sans-serif;"><span style="font-family: "arial" , "sans-serif"; line-height: 115%;"><span style="font-family: "times new roman";">
</span><span style="font-family: "arial" , "sans-serif";">In supervised learning the
data is labelled, machine learning algorithm maps the input to the desired
output to generate a model. This technique is commonly used to train neural
networks and decision trees. Neural networks are mostly applied where there is
previous data to learn from like in character recognition, image compression,
stock market prediction etc. While decision trees are also applied where
there is previous data to learn from, they are mostly applied where there are
decisions to be made like in product planning and loan applications.</span></span></span><br />
<span style="font-family: "arial" , "helvetica" , sans-serif;"><span style="font-family: "arial" , "sans-serif"; line-height: 115%;"><span style="font-family: "times new roman";">
</span></span></span><br />
<span style="font-family: "arial" , "helvetica" , sans-serif;"><span style="font-family: "arial" , "sans-serif"; line-height: 115%;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "arial" , "sans-serif";">Unsupervised learning</span></b></span></span><br />
<span style="font-family: "arial" , "helvetica" , sans-serif;"><span style="font-family: "arial" , "sans-serif"; line-height: 115%;"><span style="font-family: "times new roman";">
</span><span style="font-family: "arial" , "sans-serif";">In unsupervised learning,
machine learning algorithm<span style="color: #222222;"> </span>draws inferences
from datasets consisting of input data without labelled responses. This
technique is based on data mining methods which include clustering and latent
variable methods. Some of the unsupervised learning applications
are language understanding and image identification.</span></span></span><br />
<span style="font-family: "arial" , "helvetica" , sans-serif;"><span style="font-family: "arial" , "sans-serif"; line-height: 115%;"><span style="font-family: "times new roman";">
</span></span></span><br />
<span style="font-family: "arial" , "helvetica" , sans-serif;"><span style="font-family: "arial" , "sans-serif"; line-height: 115%;"><b style="mso-bidi-font-weight: normal;"><span style="font-family: "arial" , "sans-serif";">Active learning</span></b></span></span><br />
<span style="font-family: "arial" , "helvetica" , sans-serif;"><span style="font-family: "arial" , "sans-serif"; line-height: 115%;"><span style="font-family: "times new roman";">
</span><span style="font-family: "arial" , "sans-serif";">Active learning is a semi
supervised machine. In this technique, the learning algorithm is allowed to ask
questions from an oracle. The oracle is a human annotator which can
assign labels to training instances, in return the learner uses the feedback to
find or improve a model for the training data. They have been successfully
applied in regression testing, fuzzy testing and inference of botnet protocols.</span></span></span><br />
<span style="font-family: "arial" , "helvetica" , sans-serif;"><span style="font-family: "arial" , "sans-serif"; line-height: 115%;"><span style="font-family: "times new roman";">
</span></span></span><br />
<span style="font-family: "arial" , "helvetica" , sans-serif;"><span style="font-family: "arial" , "sans-serif"; line-height: 115%;"><strong><span style="font-family: "arial" , "sans-serif";">Transfer learning</span></strong></span></span><br />
<span style="font-family: "arial" , "helvetica" , sans-serif;"><span style="font-family: "arial" , "sans-serif"; line-height: 115%;"><span style="font-family: "times new roman";">
</span><span style="font-family: "arial" , "sans-serif";">Transfer learning system
learns models with different “source” sampling distributions and training
labels, and then transfers that knowledge to the target task<w:sdt citation="t" id="1137227095"> (Perlich,
Dalessandro, Raeder, Stitelman, & Provost, 2014)</w:sdt>.
Transfer learning attempts to change this by developing methods to transfer
knowledge learned in one or more source tasks and use it to improve learning in
a related target task<w:sdt citation="t" id="973873605"> (Torrey
& Shavlik, 2009)</w:sdt>. This technique has been
successfully applied in online advertising.</span></span></span><br />
<span style="font-family: "arial" , "helvetica" , sans-serif;"><span style="font-family: "arial" , "sans-serif"; line-height: 115%;"><span style="font-family: "times new roman";">
</span><span style="font-family: "arial" , "sans-serif";"><br />
Next we going to look at some available machine learning tools.</span></span></span></div>
<span style="font-family: "arial" , "helvetica" , sans-serif;"><span style="font-family: "arial" , "sans-serif"; line-height: 115%;">
</span></span><br />
<div style="margin: 0cm 0cm 10pt;">
<span style="font-family: "arial" , "sans-serif"; font-size: 10pt; line-height: 115%;">Reference:</span></div>
<ol style="direction: ltr; list-style-type: decimal;">
<li style="color: black; font-family: "Calibri","sans-serif"; font-size: 11pt; font-style: normal; font-weight: normal;"><div style="color: black; font-family: "Calibri","sans-serif"; font-size: 11pt; font-style: normal; font-weight: normal; margin-bottom: 10pt; margin-top: 0cm; mso-list: l0 level1 lfo1;">
<span lang="EN-US" style="mso-ansi-language: EN-US; mso-no-proof: yes;">Aarts, F., Kuppens, H., Tretmans, J., & Vaan, F. (2014).
Improving active Mealy machine learning for protocol conformance testing. <i>Machine
Learning</i>, 189-224.</span></div>
</li>
<li style="color: black; font-family: "Calibri","sans-serif"; font-size: 11pt; font-style: normal; font-weight: normal;"><div style="color: black; font-family: "Calibri","sans-serif"; font-size: 11pt; font-style: normal; font-weight: normal; margin-bottom: 0pt; margin-top: 0cm; mso-list: l0 level1 lfo1;">
<span lang="EN-US" style="mso-ansi-language: EN-US; mso-no-proof: yes;"><a href="http://www.aihorizon.com/essays/generalai/supervised_unsupervised_machine_learning.htm"><span style="color: windowtext; text-decoration: none; text-underline: none;">http://www.aihorizon.com/essays/generalai/supervised_unsupervised_machine_learning.htm</span></a></span></div>
</li>
<li style="color: black; font-family: "Calibri","sans-serif"; font-size: 11pt; font-style: normal; font-weight: normal;"><div style="color: black; font-family: "Calibri","sans-serif"; font-size: 11pt; font-style: normal; font-weight: normal; line-height: 18pt; margin-bottom: 0pt; margin-top: 0cm; mso-list: l0 level1 lfo1;">
<span lang="EN-US" style="mso-ansi-language: EN-US; mso-no-proof: yes;">Neural Networks, <a href="https://cs.stanford.edu/people/eroberts/courses/soco/projects/2000-01/neural-networks/Applications/index.html"><span style="color: windowtext; text-decoration: none; text-underline: none;">https://cs.stanford.edu/people/eroberts/courses/soco/projects/2000-01/neural-networks/Applications/index.html</span></a></span></div>
</li>
<li style="color: black; font-family: "Calibri","sans-serif"; font-size: 11pt; font-style: normal; font-weight: normal;"><div style="color: black; font-family: "Calibri","sans-serif"; font-size: 11pt; font-style: normal; font-weight: normal; line-height: 18pt; margin-bottom: 10pt; margin-top: 0cm; mso-list: l0 level1 lfo1;">
<span lang="EN-US" style="mso-ansi-language: EN-US; mso-no-proof: yes;"><a href="http://www.economistinsights.com/author/3531"><span style="color: windowtext; text-decoration: none; text-underline: none;">Pete Swabey</span></a>,
February 24th 2014, from <a href="http://www.economistinsights.com/technology-innovation/opinion/%E2%80%9Cunsupervised-learning%E2%80%9D-and-future-analytics"><span style="color: windowtext; text-decoration: none; text-underline: none;">http://www.economistinsights.com/technology-innovation/opinion/%E2%80%9Cunsupervised-learning%E2%80%9D-and-future-analytics</span></a>
targeted display advertising: transfer learning in action. Machine Learning,
103-127.</span></div>
</li>
<li style="color: black; font-family: "Calibri","sans-serif"; font-size: 11pt; font-style: normal; font-weight: normal;"><div style="color: black; font-family: "Calibri","sans-serif"; font-size: 11pt; font-style: normal; font-weight: normal; margin-bottom: 10pt; margin-top: 0cm; mso-list: l0 level1 lfo1;">
<span lang="EN-US" style="mso-ansi-language: EN-US; mso-no-proof: yes;">Torrey, L., & Shavlik, J. (2009). Transfer Learning. Handbook
of Research on Machine Learning Applications.</span></div>
</li>
<li style="color: black; font-family: "Calibri","sans-serif"; font-size: 11pt; font-style: normal; font-weight: normal;"><div style="color: black; font-family: "Calibri","sans-serif"; font-size: 11pt; font-style: normal; font-weight: normal; margin-bottom: 10pt; margin-top: 0cm; mso-list: l0 level1 lfo1;">
<span lang="EN-US" style="mso-ansi-language: EN-US; mso-no-proof: yes;">Unsupervised
learning. (2016, March 30). In Wikipedia, The Free Encyclopedia. Retrieved
13:07, May 9, 2016, from <a href="https://en.wikipedia.org/w/index.php?title=Unsupervised_learning&oldid=712692172"><span style="color: windowtext; text-decoration: none; text-underline: none;">https://en.wikipedia.org/w/index.php?title=Unsupervised_learning&oldid=712692172</span></a></span></div>
</li>
</ol>
Anonymoushttp://www.blogger.com/profile/16651671191775875167noreply@blogger.com3tag:blogger.com,1999:blog-8599851135790691075.post-20428623696249974662016-04-27T11:23:00.000-07:002016-05-11T22:07:10.721-07:00Ethics in Machine Learning - Special Post<span style="font-family: "arial" , "helvetica" , sans-serif;"><span style="font-family: "calibri"; font-size: large;">
<span style="font-family: "arial" , "sans-serif";"><span style="font-size: small;">Can't help but to mention
that as I presented on the topic on Monday 25 April, a question of ethics was
one that seriously kept me thinking. So as I was reading I came across
this link: </span><a href="http://www.kdnuggets.com/2016/03/ethics-machine-learning-tay-chatbot-fiasco.html"><span style="color: blue; font-size: small;">http://www.kdnuggets.com/2016/03/ethics-machine-learning-tay-chatbot-fiasco.html</span></a><span style="font-size: small;">.
</span></span><br />
<span style="font-family: "times new roman"; font-size: small;">
</span><br />
<span style="font-family: "arial" , "sans-serif";"><span style="font-size: small;">I think its a great
initiative, one that I would like to follow closely.</span></span><br />
<span style="font-family: "times new roman"; font-size: small;">
</span></span></span><br />
<br />
<span style="font-family: "calibri";"><span style="font-family: "calibri" , "sans-serif"; line-height: 115%;"></span></span><br />Anonymoushttp://www.blogger.com/profile/16651671191775875167noreply@blogger.com1tag:blogger.com,1999:blog-8599851135790691075.post-91756872581840289892016-04-27T11:13:00.000-07:002016-05-11T06:38:14.122-07:00New Era of Machine Learning<br />
<br />
<span style="color: black; font-family: "arial" , "sans-serif"; font-size: 12pt;"><div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="color: black; font-family: "Arial","sans-serif";">Machine has definitely shifted from the times it was based on
theory, a thing people were talking about in the corridors before yet another
conference of machine learning. More and more applications of machine
learning are now reported.</span></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<br /></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: Times New Roman;">
</span></div>
<div style="text-align: justify;">
<span style="color: black; font-family: "Arial","sans-serif";">We have seen technology
leaders like Google, Facebook, Microsoft; even banking industries implement
these powerful technologies. </span></div>
<div style="text-align: justify;">
<span style="color: black; font-family: "Arial","sans-serif";"><br /></span></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: Times New Roman;">
</span></div>
<div style="text-align: justify;">
<span style="color: black; font-family: "Arial","sans-serif";">We are now leaving in the
world that is driven by technology; everyone talks about big data, cloud
computing, adaptive security to mention few and Machine Learning seems to be
the heart of them all. Without Machine learning it would be difficult to handle
these terabytes of data and put defensive mechanisms against the ever improving
attackers. </span></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: Times New Roman;">
</span><span style="color: black; font-family: "Arial","sans-serif";"> </span></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: Times New Roman;">
</span><span style="color: black; font-family: "Arial","sans-serif";">So in this era Machine Learning is revolutionizing the world we
live in. Of great importance though is to mention that machine learning is
still based on the very algorithms that were founded in the 80’s, which makes
it a subject that is still very much dominated by academic specialist and
researchers. We see Google hiring the likes of Sebastian Thrun, Fernando
Pereira, Ray Kurzweil, all academics from different Universities. Facebook
hiring Professor Yann LeCun of NYU, and Baidu which is considered to be China’s
google hiring professor Andrew Ng from Stanford who previously worked at
Google. The completion gets tighter in this space.</span></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<br /></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: Times New Roman;">
</span></div>
<div style="text-align: justify;">
<span style="color: black; font-family: "Arial","sans-serif";"> “If you want to beat the crowd now, you have to try and buy
the people that really know this stuff—otherwise you’ll be a few years behind,”
by Michael Mozer, from Colorado University.</span></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: Times New Roman;">
</span></div>
<div style="text-align: justify;">
<span style="color: black; font-family: "Arial","sans-serif";">Let’s look forward to
discussing some of the applications of Machine Learning.</span></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: Times New Roman;">
</span></div>
<div style="text-align: justify;">
<span style="color: black; font-family: "Arial","sans-serif"; font-size: 10pt;">References:</span></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: Times New Roman;">
</span></div>
<div style="text-align: justify;">
<span style="color: black; font-family: "Arial","sans-serif"; font-size: 10pt;">Tom
Simonite,2016, <a href="https://www.technologyreview.com/s/527301/chinese-search-giant-baidu-hires-man-behind-the-google-brain/"><span style="color: black;">https://www.technologyreview.com/s/527301/chinese-search-giant-baidu-hires-man-behind-the-google-brain/</span></a></span></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: Times New Roman;">
</span></div>
<div style="text-align: justify;">
<span style="color: black; font-family: "Arial","sans-serif"; font-size: 10pt;">Josh Constine, 2013, <a href="http://techcrunch.com/2013/12/09/facebook-artificial-intelligence-lab-lecun"><span style="color: black;">http://techcrunch.com/2013/12/09/facebook-artificial-intelligence-lab-lecun</span></a></span></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<span style="font-family: Times New Roman;">
</span></div>
<div style="margin-bottom: 10pt; text-align: justify;">
<span style="font-family: Times New Roman;"><span style="font-size: 18pt;"> </span><span style="font-size: 13.5pt;"> </span> </span></div>
<div style="margin: 0cm 0cm 0pt; text-align: justify;">
<br /></div>
</span><div style="margin: 0cm 0cm 0pt; text-align: justify;">
<br /></div>
<br />Anonymoushttp://www.blogger.com/profile/16651671191775875167noreply@blogger.com2tag:blogger.com,1999:blog-8599851135790691075.post-9782997431054581222016-04-09T12:35:00.000-07:002016-05-11T06:38:40.604-07:00Methods, Challenges and Successes of Machine learning prior to the 20th Century<span style="font-family: "arial" , "helvetica" , sans-serif; font-size: large;"></span><div style="text-align: justify;">
<span style="font-family: "arial" , "helvetica" , sans-serif; font-size: large;"><span style="color: black; font-family: "arial" , "sans-serif";"><span style="font-family: "arial" , "helvetica" , sans-serif; font-size: small;"><span style="color: black; font-family: "arial" , "sans-serif";">As promised on my previous blog, let’s see what methods, challenges and successes happened in machine learning prior to 20th century.</span></span></span></span></div>
<span style="font-family: "arial" , "helvetica" , sans-serif; font-size: large;">
<span style="font-family: "times new roman"; font-size: small;">
</span></span><br />
<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><img src="http://cdn04.androidauthority.net/wp-content/uploads/2015/07/machine-learning-ai-artificial-intelligence-840x630.jpg" height="149" id="irc_mi" style="margin-left: auto; margin-right: auto; margin-top: 0px;" width="200" /></td></tr>
<tr><td class="tr-caption" style="text-align: center;"></td></tr>
</tbody></table>
<div class="MsoNormal" style="line-height: normal; margin: 0cm 0cm 10pt; mso-margin-bottom-alt: auto; mso-margin-top-alt: auto; text-align: justify;">
<span style="color: black; font-size: 18pt;"><span style="font-family: "arial" , "helvetica" , sans-serif;"><span style="color: black; font-family: "arial" , "sans-serif";"><span style="font-size: small;"><span style="color: black; font-family: "arial" , "sans-serif"; font-size: 12pt;"><span style="color: black; font-family: "arial" , "sans-serif"; font-size: 12pt;">Prior to the 20th century the idea of machine
learning was mostly knowledge driven, with a vision to automate learning by
these machines so that the knowledge could be passed to others, in a way that a
human being is unable to. This was a great idea, as we all know that
people get old and retire or they leave companies, although they can do a
handover, fact remains their knowledge and expertise always leaves with them.</span><br />
<span style="font-family: "times new roman";">
</span><br />
</span></span></span></span></span><div style="margin: 0cm 0cm 0pt; mso-line-height-alt: 0pt; text-align: justify;">
<span style="color: black; font-size: 18pt;"><span style="font-family: "arial" , "helvetica" , sans-serif;"><span style="color: black; font-family: "arial" , "sans-serif";"><span style="font-size: small;"><span style="color: black; font-family: "arial" , "sans-serif"; font-size: 12pt;"><span style="color: black; font-family: "arial" , "sans-serif"; font-size: 12pt;">Techniques like decision trees, neural networks,
multi-layered networks were used in training machines. As with any subject of
exploration machine learning was characterised by some challenges; those were</span></span></span></span></span></span></div>
<span style="color: black; font-size: 18pt;"><span style="font-family: "arial" , "helvetica" , sans-serif;"><span style="color: black; font-family: "arial" , "sans-serif";"><span style="font-size: small;"><span style="color: black; font-family: "arial" , "sans-serif"; font-size: 12pt;">
<span style="font-family: "times new roman";">
</span><br />
<div style="margin: 0cm 0cm 0pt; mso-line-height-alt: 0pt; text-align: justify;">
<span style="color: black; font-family: "arial" , "sans-serif"; font-size: 12pt;">Difficulty to get a sufficient degree of randomness
built into the structure. The expense of creating a device large enough to
exhibit behaviour not significantly influenced by the operation of any one of
its components. Slow response, theoretical limitations and not enough data to
learn from.</span></div>
<span style="font-family: "times new roman";">
</span><br />
<div style="margin: 0cm 0cm 0pt; mso-line-height-alt: 0pt; text-align: justify;">
<span style="color: black; font-family: "arial" , "sans-serif"; font-size: 12pt;">Despite all these there were some instances of
success that were reported like the use of chaostron by the U.S. Navy for
controlling their inventory, application of decision trees to industrial
process controls and the integration of explanation-based learning into general
knowledge-intensive reasoning systems.</span></div>
<span style="font-family: "times new roman";">
</span><br />
<div style="margin: 0cm 0cm 0pt; mso-line-height-alt: 0pt; text-align: justify;">
<span style="color: black; font-family: "arial" , "sans-serif"; font-size: 12pt;">After all was there still potential for advancement
in machine learning. Let’s find out in our next episode.</span></div>
<span style="font-family: "times new roman";">
</span><br />
<div style="margin: 0cm 0cm 0pt; mso-line-height-alt: 0pt; text-align: justify;">
<span style="color: black; font-family: "arial" , "sans-serif"; font-size: 10pt;">References:</span></div>
<span style="font-family: "times new roman";">
</span><br />
<div style="margin: 0cm 0cm 0pt; mso-line-height-alt: 0pt; text-align: justify;">
<span style="color: black; font-family: "arial" , "sans-serif"; font-size: 10pt;">CADWALLADER-COHEN, J.,
ZYSICZK , W., & DONNELLY, R. (1984). THE CHAOSTRON: AN IMPORTANT ADVANCE IN
LEARNING MACHINES. Communications of the ACM, 356-357.<br />
Carbonell, J. G. (1989). Introduction: Paradigms for Machine Learning. <i>Elsevier
Science Publisher</i>, 1-9.</span></div>
<span style="font-family: "times new roman";">
</span><span style="color: black; font-family: "arial" , "sans-serif"; font-size: 10pt;">Jones, R. M., &
Taube, M. (1961). Notes on distinction between character recognition machines
and percieving machines. <i>American Documentations</i>, 292.</span><br />
<span style="font-family: "times new roman";">
</span><br />
<div style="margin: 0cm 0cm 0pt; mso-line-height-alt: 0pt; text-align: justify;">
<span style="color: black; font-family: "arial" , "sans-serif"; font-size: 18pt;"> </span></div>
<span style="font-family: "times new roman";">
</span><br />
<div style="margin: 0cm 0cm 0pt; mso-line-height-alt: 0pt; text-align: justify;">
<span style="color: black; font-family: "arial" , "sans-serif"; font-size: 18pt;"> </span></div>
<span style="font-family: "times new roman";">
</span><br />
<div style="margin: 0cm 0cm 0pt; mso-line-height-alt: 0pt; text-align: justify;">
<span style="color: black; font-family: "times new roman" , "serif"; font-size: 18pt;"> </span></div>
<span style="font-family: "times new roman";">
</span></span></span></span></span></span><br />
<br />
<br /></div>
<br />Anonymoushttp://www.blogger.com/profile/16651671191775875167noreply@blogger.com1tag:blogger.com,1999:blog-8599851135790691075.post-29749629702805859402016-03-25T03:31:00.003-07:002016-05-11T06:39:08.297-07:00<h2 style="text-align: center;">
What is Machine Learning ?</h2>
<div style="text-align: justify;">
<span style="color: black; font-family: "calibri"; font-size: 18pt;"></span> <span style="color: black; font-family: "calibri"; font-size: 18pt;"><a href="data:image/jpeg;base64,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" imageanchor="1" style="clear: left; 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<span style="color: black; font-family: "calibri"; font-size: 18pt;"><span style="color: black; font-size: 18pt;"><span style="color: black; font-family: "arial" , "sans-serif"; font-size: 12pt;">Machine learning is a computerised data analysis based on methods like
Decision Trees, D3 and Neural Networks that learns large amounts
of data and interpret and make predictions without being
supervised.</span></span></span></div>
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<span style="color: black; font-family: "calibri"; font-size: 18pt;"><span style="color: black; font-size: 18pt;"><span style="color: black; font-family: "arial" , "sans-serif"; font-size: 12pt;">There is currently an increase in the number of research done by
both practitioners and academics on this topic. The increasing
trend is confirmed by the likes of Gardner, listing Advanced Machine
Learning as one of the top 10 information technology trends for 2016.</span></span></span></div>
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<span style="color: black; font-family: "arial" , "sans-serif"; font-size: 12pt;">The question that comes in one's mind is how much improvement has
been made in machine learning since the times of Robert,1961 when he reported
that an International conference held by UNESCO in 1959 had dedicated the whole
section on machine learning. In 1989, Carbonell also reported in his
research that there has been an annual conference dedicated to machine
learning. Both authors also mentioned the increase in articles that were
published in the topic. </span></div>
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<span style="color: black; font-family: "arial" , "sans-serif"; font-size: 12pt;">This clearly tells us that the concept of machine learning has always
been of interest and one that promises improvement in how data is analysed,
interpreted and used.</span></div>
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<span style="color: black; font-family: "arial" , "sans-serif"; font-size: 12pt;">This blog is dedicated to uncovering the journey of machine learning. </span></div>
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<span style="color: black; font-family: "arial" , "sans-serif"; font-size: 12pt;">The next episode will talk about the methods, successes,
challenges and learning of machine learning prior to the 20th century.</span></div>
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