Here are some interesting, (some even a bit funny) short videos explaining Data Science/Machine Learning. I will be adding to this periodically as I come across more: Weird Introduction Deep Learning Using Tensorflow Keep Farmers Happy and Cows Healthy Data Science - Eindhoven University of Technology

These online articles a great hands-on introduction to the Machine Learning principles, including the Mathematics background and theoretical principles. You can even follow along, getting started with Python to see ML at work. Mathematics for Data Science Basic Linear Algebra for Deep Learning Linear Algebra Cheat Sheet Linear Algebra for Deep Learning (includes some Python) Developing in Python Python programming Quick dive into Pandas for Data Science The Four Pillars of O

There are many methods for doing automated Machine Learning. Early methods modeled biological or statistical building blocks in low level procedural code. The programming methodologies have evolved over the years to have libraries of the building blocks built and packaged for convenience. Even at a higher level, whole platforms have been packaged and provided in such a way that almost drag and drop methods can be used, with parameter choice made at different levels of automat

As a researcher at Georgia Institute of Technology, I applied Artificial Neural Networks to Semiconductor Manufacturing and co-authored the following articles under Dr. Gary S. May. Dr. May went on to head the Electrical and Computer Engineering department at Tech, and then became Dean of College of Engineering. In February, 2017 he was appointed the Chancellor of the University of California at Davis. Google Scholars on Christopher Himmel Advantages of plasma etch modeling u