Anglický jazyk

TENSORFLOW MACHINE LEARNING CK

Na objednávku, dodanie 2-4 týždne

61.25 €

bežná cena: 69.60 €

O knihe

Explore machine learning concepts using the latest numerical computing library - TensorFlow - with the help of this comprehensive cookbook
Key Features

Your quick guide to implementing TensorFlow in your day-to-day machine learning activities

Learn advanced techniques that bring more accuracy and speed to machine learning

Upgrade your knowledge to the second generation of machine learning with this guide on TensorFlow

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 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.

What you will learn

Become familiar with the basics of the TensorFlow machine learning library

Get to know Linear Regression techniques with TensorFlow

Learn SVMs with hands-on recipes

Implement neural networks and improve predictions

Apply NLP and sentiment analysis to your data

Master CNN and RNN through practical recipes

Take TensorFlow into production

Who this book is for

This book is ideal for data scientists who are familiar with C++ or Python and perform machine learning activities on a day-to-day basis. Intermediate and advanced machine learning implementers who need a quick guide they can easily navigate will find it useful.