Machine Learning with TensorFlow

TensorFlow, Google's library for large-scale machine learning, simplifies often-complex computations by representing them as graphs and efficiently mapping parts of the graphs to machines in a cluster or to the processors of a single machine.

This book gives readers a solid foundation in machine-learning concepts plus hands-on experience coding TensorFlow with Python. You'll learn the basics by working with classic prediction, classification, and clustering algorithms. Then, you'll move on to the money chapters: exploration of deep-learning concepts like autoencoders, recurrent neural networks, and reinforcement learning. Digest this book and you will be ready to use TensorFlow for machine-learning and deep-learning applications of your own.

Pages : 227 pages
Size : HTML
File type : pdf
Downloads: 15
Created: 2020-08-29
License: Free to read online (entire book) by the publisher.
Author(s): Nishant Shukla
Machine Learning with TensorFlow

Warning: Trying to access array offset on false in /home/tutovnfz/public_html/article.php on line 233

Others Machine learning Tutorials

Overview of Machine Learning

Machine Learning Yearning

Machine Learning: The Complete Guide

Interpretable Machine Learning

Python Machine Learning Projects

Others related eBooks about Machine Learning with TensorFlow

Mathematics for Computer Science

This book covers elementary discrete mathematics for computer science and engineering. It emphasizes mathematical definitions and proofs as well as applicable methods. It explores the topics of basic combinatorics, number and graph theory, logic and proof techniques, and many more....

A Problem Course in Mathematical Logic

A Problem Course in Mathematical Logic is intended to serve as the text for an introduction to mathematical logic for undergraduates with some mathematical sophistication. It supplies definitions, statements of results, and problems, along with some explanations, examples, and hints. The idea is for...

Introduction to Probability, Statistics, and Random Processes

This book introduces students to probability, statistics, and stochastic processes. It can be used by both students and practitioners in engineering, various sciences, finance, and other related fields. It provides a clear and intuitive approach to these topics while maintaining mathematical accur...

Assembler Computing system

This tutorial contain a basics informations about assembler and elements of computing systems ,a free training document under 22 pages for download....

Software & Hardware Collide

Download free course Software & Hardware Collide, pdf file on 80 pages by Jon Bruner, Glen Martin, Matthew Gast, Tim O'Reilly, Kipp Bradford, Jim Stogdill, Andy Fitzgerald....

Beginners guide to Adobe Photoshop

Welcome to the complete beginners guide to Adobe Photoshop.It's a free PDF file under 44 pages by TastyTuts....

An Introduction to Matlab and Mathcad

Download free course An Introduction to Matlab and Mathcad, pdf file on 136 pages by by Troy Siemers....

The Privacy Engineer's Manifesto

The Privacy Engineer's Manifesto: Getting from Policy to Code to QA to Value is the first ..., download free Manifesto tutorial in PDF (400 pages) created by Michelle Finneran Dennedy ....

Automated Machine Learning

This book presents the first comprehensive overview of general methods in Automated Machin..., download free Machine Learning tutorial in PDF (220 pages) created by Frank Hutter ....

3D Rendering: An Introduction

3D rendering is the 3D computer graphics process of automatically converting 3D wire frame models into 2D images with 3D photorealistic effects or non-photorealistic rendering on a computer. Rendering is the final process of creating the actual 2D image or animation from the prepared scene. ...