Hands-On Deep Learning for Images with TensorFlow

What this book covers

Chapter 1, Machine Learning Toolkit, looks into installing Docker, setting up a machine learning Docker file, sharing data back with your host computer, and running a REST service to provide the environment.

Chapter 2, Image Data, teaches MNIST digits, how to acquire them, how tensors are really just multidimensional arrays, and how we can encode image data and categorical or classification data as a tensor. Then, we have a quick review and a cookbook approach to consider dimensions and tensors, in order to get data prepared for machine learning.

Chapter 3, Classical Neural Network, covers an awful lot of material! We see the structure of the classical, or dense, neural network. We learn about activation, nonlinearity, ...