Optimization, Machine Learning Models, and TensorFlow

This is Part 2 of a four-part series that breaks up a talk that Seth Juarez gave at the Toronto AI Meetup. (Watch Part 1)

Index:

  • [00:13] Optimization (I explain calculus!!!)
  • [04:40] Gradient descent
  • [06:26] Perceptron (or linear models – we learned what these are in part 1 but I expound a bit more)
  • [07:04] Neural Networks (as an extension to linear models)
  • [09:28] Brief Review of TensorFlow

Frank

#DataScientist, #DataEngineer, Blogger, Vlogger, Podcaster at http://DataDriven.tv . Back @Microsoft to help customers leverage #AI Opinions mine. #武當派 fan. I blog to help you become a better data scientist/ML engineer Opinions are mine. All mine.