Book Image

TensorFlow Machine Learning Cookbook - Second Edition

By : Nick McClure, Sujit Pal
Book Image

TensorFlow Machine Learning Cookbook - Second Edition

By: Nick McClure, Sujit Pal

Overview of this book

TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and allow you to dig deeper and gain more insights into your data than ever before. With the help of this book, you will work with recipes for training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and more. You will explore RNNs, CNNs, GANs, reinforcement learning, and capsule networks, each using Google's machine learning library, TensorFlow. Through real-world examples, you will get hands-on experience with linear regression techniques with TensorFlow. Once you are familiar and comfortable with the TensorFlow ecosystem, you will be shown how to take it to production. By the end of the book, you will be proficient in the field of machine intelligence using TensorFlow. You will also have good insight into deep learning and be capable of implementing machine learning algorithms in real-world scenarios.
Table of Contents (13 chapters)

Understanding loss functions in linear regression

It is important to know the effect of loss functions in algorithm convergence. Here, we will illustrate how the L1 and L2 loss functions affect convergence in linear regression.

Getting ready

We will use the same iris data set as in the prior recipe, but we will change our loss functions and learning rates to see how convergence changes.

How to do it...

We proceed with the recipe as follows:

  1. The start of the program is the same as the last recipe, until we get to our loss function. We load the necessary libraries, start...