Intro to TensorFlow (source: O'Reilly) Join expert Aurélien Géron for a hands-on, in-depth exploration of TensorFlow. In this course, you’ll learn how to use TensorFlow to build, train and run state-of-the-art Deep Learning systems.
In the first part of this course, you will learn the fundamentals of TensorFlow, such as computational graphs, auto-differentiation, sessions, placeholders and more. You will then learn how to apply this knowledge by building a simple logistic regression classifier, training it using stochastic gradient descent, and running it to make predictions. In the process you will also get a brief introduction (or reminder) to some of the fundamental concepts of Machine Learning, such as training sets/test sets, overfitting, cost function and gradient descent. In the second part of this course, you will learn about deep neural networks and techniques to train them efficiently using TensorFlow.