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TensorFlow Machine Learning Cookbook Second Edition

This is the code repository for TensorFlow Machine Learning Cookbook Second Edition, published by Packt.

Over 60 recipes to build intelligent machine learning systems with the power of Python

What is this book about?

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.

This book covers the following exciting features: <First 5 What you'll learn points>

Become familiar with the basic features of the TensorFlow library
Get to know Linear Regression techniques with TensorFlow
Learn SVMs with hands-on recipes
Implement neural networks to improve predictive modeling
Apply NLP and sentiment analysis to your data

If you feel this book is for you, get your copy today!

Instructions and Navigations

All of the code is organized into folders. For example, Chapter02.

The code will look like the following:

embedding_matrix = tf.Variable(tf.random_uniform([n, m], -1.0, 1.0))
embedding_output = tf.nn.embedding_lookup(embedding_matrix,
x_data_placeholder)

Following is what you need for this book: If you are a data scientist or a machine learning engineer with some knowledge of linear algebra, statistics, and machine learning, this book is for you. If you want to skip the theory and build production-ready machine learning models using Tensorflow without reading pages and pages of material, this book is for you. Some background in Python programming is assumed.

With the following software and hardware list you can run all code files present in the book (Chapter 1-15).

Software and Hardware List

Chapter	Software required	OS required
All	tensorflow>=1.10.0	Windows, Mac OS X, and Linux (Any)
	matplotlib==2.2.2	Windows, Mac OS X, and Linux (Any)
	six==1.11.0	Windows, Mac OS X, and Linux (Any)
	requests==2.18.4	Windows, Mac OS X, and Linux (Any)
	tensorflow_serving_api==1.9.0	Windows, Mac OS X, and Linux (Any)
	numpy==1.14.5	Windows, Mac OS X, and Linux (Any)
	scipy==1.1.0	Windows, Mac OS X, and Linux (Any)
	grpcio==1.14.1	Windows, Mac OS X, and Linux (Any)
	jupyter_core==4.4.0	Windows, Mac OS X, and Linux (Any)
	Pillow==5.2.0	Windows, Mac OS X, and Linux (Any)
	GitPython==2.1.11	Windows, Mac OS X, and Linux (Any)
	grpc==0.3-19	Windows, Mac OS X, and Linux (Any)
	nltk==3.3	Windows, Mac OS X, and Linux (Any)
	skimage==0.0	Windows, Mac OS X, and Linux (Any)
	Rscikit_learn==0.19.2	Windows, Mac OS X, and Linux (Any)

Get to Know the Author(s)

Nick McClure Nick McClure is currently a senior data scientist at PayScale, Inc. in Seattle, WA. Prior to this, he has worked at Zillow Group and Caesar's Entertainment Corporation. He got his degrees in Applied Mathematics from The University of Montana and the College of Saint Benedict and Saint John's University. He has a passion for learning and advocating for analytics, machine learning, and artificial intelligence. Nick occasionally puts his thoughts and musings on his blog, fromdata.org, or through his Twitter account, @nfmcclure.

Other books by the authors

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