Need help with TensorFlow-Machine-Learning-Cookbook?
Click the “chat” button below for chat support from the developer who created it, or find similar developers for support.

About the developer

545 Stars 400 Forks MIT License 19 Commits 0 Opened issues


Code repository for TensorFlow Machine Learning Cookbook by Packt

Services available


Need anything else?

Contributors list

TensorFlow Machine Learning Cookbook

This is the code repository for TensorFlow Machine Learning Cookbook, published by Packt. It contains all the supporting project files necessary to work through the book from start to finish.

About the 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 will let you dig deeper and gain more insights into your data than ever before. You’ll work through recipes on training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and deep learning – each using Google’s machine learning library TensorFlow.

This guide starts with the fundamentals of the TensorFlow library which includes variables, matrices, and various data sources. Moving ahead, you will get hands-on experience with Linear Regression techniques with TensorFlow. The next chapters cover important high-level concepts such as neural networks, CNN, RNN, and NLP.

Once you are familiar and comfortable with the TensorFlow ecosystem, the last chapter will show you how to take it to production.

Instructions and Navigations

All of the code is organized into folders. Each folder starts with a number followed by the application name. For example, Chapter 03.

The code will look like the following:

     import matplotlib.pyplot as plt
     import numpy as np
     import tensorflow as tf
     from sklearn import datasets
     from tensorflow.python.framework import ops

Software requirements:

Python 3, with the following installed Python libraries: TensorFlow, Numpy, Scikit-Learn, Requests, and Jupyter. It is compatible in all three major operating systems, Mac, Windows, and Linux. It requires no special hardware to run the scripts.

Related Products:

Suggestions and Feedback

Click here if you have any feedback or suggestions.

We use cookies. If you continue to browse the site, you agree to the use of cookies. For more information on our use of cookies please see our Privacy Policy.