Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
Deep Learning with TensorFlow: Explore neural networks and build intelligent systems with Python, 2nd Edition


Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow.

Key Features

  • Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow
  • Explore deep neural networks and layers of data abstraction with the help of this comprehensive guide
  • Gain real-world contextualization through some deep learning problems concerning research and application

Book Description

Deep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, which are at the core of deep learning, are being used in predictive analytics, computer vision, natural language processing, time series forecasting, and to perform a myriad of other complex tasks.

This book is conceived for developers, data analysts, machine learning practitioners and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open source Python libraries.

Throughout the book, you'll learn how to develop deep learning applications for machine learning systems using Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Autoencoders, and Factorization Machines. Discover how to attain deep learning programming on GPU in a distributed way.

You'll come away with an in-depth knowledge of machine learning techniques and the skills to apply them to real-world projects.

What you will learn

  • Apply deep machine intelligence and GPU computing with TensorFlow
  • Access public datasets and use TensorFlow to load, process, and transform the data
  • Discover how to use the high-level TensorFlow API to build more powerful applications
  • Use deep learning for scalable object detection and mobile computing
  • Train machines quickly to learn from data by exploring reinforcement learning techniques
  • Explore active areas of deep learning research and applications

Who This Book Is For

The book is for people interested in machine learning and machine intelligence. A rudimentary level of programming in one language is assumed, as is a basic familiarity with computer science techniques and technologies, including a basic awareness of computer hardware and algorithms. Some competence in mathematics is needed to the level of elementary linear algebra and calculus.

Table of Contents

  1. Getting Started with Deep Learning
  2. A First Look at TensorFlow
  3. Feed-Forward Neural Networks with TensorFlow
  4. Convolutional Neural Networks
  5. Optimizing TensorFlow Autoencoders
  6. Recurrent Neural Networks
  7. Heterogeneous and Distributed Computing
  8. Advanced TensorFlow Programming
  9. Recommendation Systems using Factorization Machines
  10. Reinforcement Learning
(HTML tags aren't allowed.)

JavaScript Simplified: JavaScript Simplified And Turned To Fun (Web Development Simplified)
JavaScript Simplified: JavaScript Simplified And Turned To Fun (Web Development Simplified)

This book is simplified version to make you fully understand JavaScript. This book is simple enough to make you fully understand JavaScript  and ES6 without wasting your time and buggle your brain with complex theories or explanations. This book is fully practical in nature and simplified...

Lehninger Principles of Biochemistry, Fourth Edition
Lehninger Principles of Biochemistry, Fourth Edition
The fourth edition of Lehninger Principles of Biochemistry stays true to the vision of its predecessors while embracing the advances made in biochemical research since the previous edition. As always, the book presents the fundamentals of biochemistry through selected topics, and emphasizes the most important recent developments and applications...
Traffic Engineering with MPLS
Traffic Engineering with MPLS

Design, configure, and manage MPLS TE to optimize network performance.

Almost every busy network backbone has some congested links while others remain underutilized. That's because shortest-path routing protocols send traffic down the path that is shortest without considering other network parameters,...

Unleashing Web 2.0: From Concepts to Creativity
Unleashing Web 2.0: From Concepts to Creativity
Dr. Gottfried Vossen and Stephen Hagemann have very clearly explained the transition to the new read/write era of the Webalso known as Web 2.0. This book will help you understand the ongoing evolution of the Web, and push you to create applications that take advantage of the read/write Web. Richard MacManus, Editor, Read/WriteWeb...
PDF Hacks : 100 Industrial-Strength Tips &Tools
PDF Hacks : 100 Industrial-Strength Tips &Tools

Many people think of Adobe's Portable Document Format (PDF) as a proprietary format for delivering unchangeable content that readers can print out or view on-screen conveniently. That may be how most people work with it, but you can do many more things with PDF, with or without Adobe's tools.

PDF has...

Layer 2 VPN Architectures (Networking Technology)
Layer 2 VPN Architectures (Networking Technology)

Master the world of Layer 2 VPNs to provide enhanced services and enjoy productivity gains

  • Learn about Layer 2 Virtual Private Networks (VPNs)

  • Reduce costs and extend the reach of your services by unifying your network architecture

©2021 LearnIT (support@pdfchm.net) - Privacy Policy