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Jose Portilla
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Job Title:
Head of Data Science
Job Function:
Data Science, Machine Learning, AI, Business Analytics, Deep Learning
Short Bio:
Jose Marcial Portilla has a BS and MS in Mechanical Engineering from Santa Clara University and years of experience as a professional instructor and trainer for Data Science and programming. He has publications and patents in various fields such as microfluidics, materials science, and data science technologies. Over the course of his career he has developed a skill set in analyzing data and he hopes to use his experience in teaching and data science to help other people learn the power of programming the ability to analyze data, as well as present the data in clear and beautiful visualizations. Currently he works as the Head of Data Science for Pierian Data Inc. and provides in-person data science and python programming training courses to employees working at top companies, including General Electric, Cigna, The New York Times, Credit Suisse, and many more. Feel free to contact him on LinkedIn for more information on in-person training sessions or group training sessions in Las Vegas, NV.
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At 1:36pm on November 3, 2017, Hector Alvaro Rojas said…

Hi, José:


What’s up?


I went through your article and I liked it a lot.  Congratulations!


Anyway, I have two questions about this article that I would like to ask you kindly:


1)      How can connect the “confusionMatrix()” option from “Caret” library to this neural net application, so I can get all the outputs that confusionMatrix() offer?


2)      Do you know a way to get “K fold cross-validation” applied here too ( using “neuralnet” package not “nnet”)?  I would like to get this done and get averages and sd (standard deviation) results for accuracy, roc, f1, recall, sensitivity specitivity metrics at the same time.


3)      So far I know, Caret library does not support “neuralnet” as a method for neural network modeling.  Do you know a way to use “neuralnet” with Caret library?


I have been doing some google research but so far I still do not find a clear answer to this questions.


I hope you can give me some help.







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