<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" version="2.0">
  <channel>
    <title>topic Re: Module 4: Neural Network - seeking advice in SAS Academy for Data Science</title>
    <link>https://communities.sas.com/t5/SAS-Academy-for-Data-Science/Module-4-Neural-Network-seeking-advice/m-p/450801#M104</link>
    <description>&lt;P&gt;Hey Jeff,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;That's a great question...&amp;nbsp; If time is limited and I need a quick model, then I typically run several variations of neural network node and use a model comparison node to select a champion model.&amp;nbsp; If I have the time, then I prefer to use PROC NEURAL because I have greater control over how the model is designed.&amp;nbsp; For example, I can control the feedforward connections in the neural network, I can add additional hidden layers, train&amp;nbsp;using a variable learning rate schedule, etc..&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I'd recommend taking the time to learn to code using PROC NEURAL.&amp;nbsp; You'll likely have to tackle problems that do not conform or fit into a nice, neat box - You'll need the coding skills to create a customized solution.&amp;nbsp; Also, SAS Viya's PROC NNET is closely modeled after PROC NEURAL.&amp;nbsp; So learning one will make it very easy to learn the other.&amp;nbsp; Two birds as they say..&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Best,&lt;/P&gt;
&lt;P&gt;&amp;nbsp; Robert W. Blanchard&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Tue, 03 Apr 2018 18:50:48 GMT</pubDate>
    <dc:creator>RobertBlanchard</dc:creator>
    <dc:date>2018-04-03T18:50:48Z</dc:date>
    <item>
      <title>Module 4: Neural Network - seeking advice</title>
      <link>https://communities.sas.com/t5/SAS-Academy-for-Data-Science/Module-4-Neural-Network-seeking-advice/m-p/450461#M100</link>
      <description>&lt;P&gt;Hi,&lt;/P&gt;&lt;P&gt;I am currently taking Module 4: Advanced Predictive Modeling and looking for advice from anyone who has completed that course and the associated certification exam. Whereas the logistic regression section had a lot of explanations and justifications for why certain techniques were used, the neural network section primarily seems to be assessing how well I can duplicate the instructor's steps in Enterprise Miner with very little explanation. Additionally, the neural network course has no end-of-chapter quizzes to assess whether or not key points have been learned.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I'm looking for suggestions for how to supplement my neural network education in preparation for the exam.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thanks!&lt;/P&gt;</description>
      <pubDate>Mon, 02 Apr 2018 21:09:58 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Academy-for-Data-Science/Module-4-Neural-Network-seeking-advice/m-p/450461#M100</guid>
      <dc:creator>Jeff_RNL</dc:creator>
      <dc:date>2018-04-02T21:09:58Z</dc:date>
    </item>
    <item>
      <title>Re: Module 4: Neural Network - seeking advice</title>
      <link>https://communities.sas.com/t5/SAS-Academy-for-Data-Science/Module-4-Neural-Network-seeking-advice/m-p/450700#M102</link>
      <description>&lt;P&gt;Hey Jeff,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;First, congratulations on your journey to becoming a SAS Certified Data Scientist.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I understand your frustration with the design of the course, in that certain actions are performed in some demonstrations before the related content is described - I sympathies.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;The exam content was created with the neural network course in mind.&amp;nbsp; Therefore, I would recommend focusing most of your time studying the course, as opposed to seeking supplemental material.&amp;nbsp; I suggest&amp;nbsp;you &lt;STRONG&gt;rework through the course&lt;/STRONG&gt; and make sure you understand why actions are being performed.&amp;nbsp; For example, in the Compositional Data demonstration (ch. 2),&amp;nbsp;be sure you know why the softmax activation function was used in the output layer... and why the cross-entropy error function is used.&amp;nbsp; If you are unsure as to why these options are being chosen, then navigate to the activation function and error function sections - investigate and become comfortable with why those option values were chosen.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I would also highly recommend taking the practice exam after you have become comfortable with the course material. &amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;All of the above stated, a practitioner that has used neural networks for years, or a researcher that focuses on neural networks should be able to pass the exam without taking the course.&amp;nbsp; If you would like to dive deeper into subject areas as preparation for the exam, I would recommend the reference section in the appendix of the course.&amp;nbsp; I'm directing your attention to the reference section as opposed to the broader internet because the course was built from the works of the referenced authors/researchers.&amp;nbsp; And again, the exam content was created with the neural network course in mind... &amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;A closing thought - I think you'll do well on the neural network section of the exam.&amp;nbsp; Some of my past SAS Academy for Data Science students expressed that they scored highest on the neural network section. &amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I'm here to help if you have other questions.&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;All the best and good luck,&lt;/P&gt;
&lt;P&gt;&amp;nbsp; Robert W. Blanchard&lt;/P&gt;</description>
      <pubDate>Tue, 03 Apr 2018 15:17:22 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Academy-for-Data-Science/Module-4-Neural-Network-seeking-advice/m-p/450700#M102</guid>
      <dc:creator>RobertBlanchard</dc:creator>
      <dc:date>2018-04-03T15:17:22Z</dc:date>
    </item>
    <item>
      <title>Re: Module 4: Neural Network - seeking advice</title>
      <link>https://communities.sas.com/t5/SAS-Academy-for-Data-Science/Module-4-Neural-Network-seeking-advice/m-p/450765#M103</link>
      <description>&lt;P&gt;Thanks so much for your response and advice.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I'm curious about something...the Neural Network module has a pretty good balance of models built with the Enterprise Miner Neural Network node as well as models built in a code node using PROC NEURAL. Which approach do you prefer in practice?&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Jeff&lt;/P&gt;</description>
      <pubDate>Tue, 03 Apr 2018 17:53:59 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Academy-for-Data-Science/Module-4-Neural-Network-seeking-advice/m-p/450765#M103</guid>
      <dc:creator>Jeff_RNL</dc:creator>
      <dc:date>2018-04-03T17:53:59Z</dc:date>
    </item>
    <item>
      <title>Re: Module 4: Neural Network - seeking advice</title>
      <link>https://communities.sas.com/t5/SAS-Academy-for-Data-Science/Module-4-Neural-Network-seeking-advice/m-p/450801#M104</link>
      <description>&lt;P&gt;Hey Jeff,&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;That's a great question...&amp;nbsp; If time is limited and I need a quick model, then I typically run several variations of neural network node and use a model comparison node to select a champion model.&amp;nbsp; If I have the time, then I prefer to use PROC NEURAL because I have greater control over how the model is designed.&amp;nbsp; For example, I can control the feedforward connections in the neural network, I can add additional hidden layers, train&amp;nbsp;using a variable learning rate schedule, etc..&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;I'd recommend taking the time to learn to code using PROC NEURAL.&amp;nbsp; You'll likely have to tackle problems that do not conform or fit into a nice, neat box - You'll need the coding skills to create a customized solution.&amp;nbsp; Also, SAS Viya's PROC NNET is closely modeled after PROC NEURAL.&amp;nbsp; So learning one will make it very easy to learn the other.&amp;nbsp; Two birds as they say..&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Best,&lt;/P&gt;
&lt;P&gt;&amp;nbsp; Robert W. Blanchard&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Tue, 03 Apr 2018 18:50:48 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Academy-for-Data-Science/Module-4-Neural-Network-seeking-advice/m-p/450801#M104</guid>
      <dc:creator>RobertBlanchard</dc:creator>
      <dc:date>2018-04-03T18:50:48Z</dc:date>
    </item>
  </channel>
</rss>

