Skip the theory and get the most out of Tensorflow to build productionready machine learning models
Key Features

Exploit the features of Tensorflow to build and deploy machine learning models

Train neural networks to tackle realworld problems in Computer Vision and NLP

Handy techniques to write productionready code for your Tensorflow models
Book Description
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 realworld examples, you will get handson 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 realworld scenarios.
What you will learn

Become familiar with the basic features of the TensorFlow library

Get to know Linear Regression techniques with TensorFlow

Learn SVMs with handson recipes

Implement neural networks to improve predictive modeling

Apply NLP and sentiment analysis to your data

Master CNN and RNN through practical recipes

Implement the gradient boosted random forest to predict housing prices

Take TensorFlow into production
Who this book is for
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 productionready machine learning models using Tensorflow without reading pages and pages of material, this book is for you. Some background in Python programming is assumed.
Table of Contents

Getting Started with TensorFlow

The TensorFlow Way

Linear Regression

Support Vector Machines

Nearest Neighbor Methods

Neural Networks

Natural Language Processing

Convolutional Neural Networks

Recurrent Neural Networks

Taking TensorFlow to Production

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