In this chapter, we will cover the basic recipes for understanding how TensorFlow works and how to access data for this book and additional resources. We will cover the following areas:
Using the Matrix Inverse Method
Implementing a Decomposition Method
Learning the TensorFlow Way of Regression
Understanding Loss Functions in Linear Regression
Implementing Deming Regression
Implementing Lasso and Ridge Regression
Implementing Elastic Net Regression
Implementing Regression Logistic Regression