Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow, 2nd Edition

Buy

Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries

Key Features

  • Build a strong foundation in neural networks and deep learning with Python libraries
  • Explore advanced deep learning techniques and their applications across computer vision and NLP
  • Learn how a computer can navigate in complex environments with reinforcement learning

Book Description

With the surge in artificial intelligence in applications catering to both business and consumer needs, deep learning is more important than ever for meeting current and future market demands. With this book, you'll explore deep learning, and learn how to put machine learning to use in your projects.

This second edition of Python Deep Learning will get you up to speed with deep learning, deep neural networks, and how to train them with high-performance algorithms and popular Python frameworks. You'll uncover different neural network architectures, such as convolutional networks, recurrent neural networks, long short-term memory (LSTM) networks, and capsule networks. You'll also learn how to solve problems in the fields of computer vision, natural language processing (NLP), and speech recognition. You'll study generative model approaches such as variational autoencoders and Generative Adversarial Networks (GANs) to generate images. As you delve into newly evolved areas of reinforcement learning, you'll gain an understanding of state-of-the-art algorithms that are the main components behind popular games Go, Atari, and Dota.

By the end of the book, you will be well-versed with the theory of deep learning along with its real-world applications.

What you will learn

  • Grasp the mathematical theory behind neural networks and deep learning processes
  • Investigate and resolve computer vision challenges using convolutional networks and capsule networks
  • Solve generative tasks using variational autoencoders and Generative Adversarial Networks
  • Implement complex NLP tasks using recurrent networks (LSTM and GRU) and attention models
  • Explore reinforcement learning and understand how agents behave in a complex environment
  • Get up to date with applications of deep learning in autonomous vehicles

Who this book is for

This book is for data science practitioners, machine learning engineers, and those interested in deep learning who have a basic foundation in machine learning and some Python programming experience. A background in mathematics and conceptual understanding of calculus and statistics will help you gain maximum benefit from this book.

Table of Contents

  1. Machine Learning – An Introduction
  2. Neural Networks
  3. Deep Learning Fundamentals
  4. Computer Vision With Convolutional Networks
  5. Advanced Computer Vision
  6. Generating images with GANs and Variational Autoencoders
  7. Recurrent Neural Networks and Language Models
  8. Reinforcement Learning Theory
  9. Deep Reinforcement Learning for Games
  10. Deep Learning in Autonomous Vehicles
(HTML tags aren't allowed.)

Spark for Python Developers
Spark for Python Developers

Key Features

  • Set up real-time streaming and batch data intensive infrastructure using Spark and Python
  • Deliver insightful visualizations in a web app using Spark (PySpark)
  • Inject live data using Spark Streaming with real-time events

Book Description

Looking...

Data Stewardship: An Actionable Guide to Effective Data Management and Data Governance
Data Stewardship: An Actionable Guide to Effective Data Management and Data Governance

Data stewards in business and IT are the backbone of a successful data governance implementation because they do the work to make a company’s data trusted, dependable, and high quality. Data Stewardship explains everything you need to know to successfully implement the stewardship portion of data governance, including how to...

The Analyst Application
The Analyst Application
This guide will show you how to use the Analyst Application to perform such tasks as table analysis, ANOVA, repeated measurements, mixed models, basic power computations, and much more.

Discover how to perform statistical analysis using the Analyst Application, a point-and-click interface to basic statistical analysis in SAS. The
...

Mac Application Development by Example Beginner's Guide
Mac Application Development by Example Beginner's Guide

It's never been more important to have the ability to develop an App for Mac OS X. Whether it's a System Preference, a business app that accesses information in the Cloud, or an application that uses multi-touch or uses a camera, you will have a solid foundation in app development to get the job done.

Mac Application...

Professional SharePoint 2010 Development
Professional SharePoint 2010 Development

Learn to leverage the features of the newest version of SharePoint, in this update to the bestseller

More than simply a portal, SharePoint is Microsoft's popular content management solution for building intranets and Web sites or hosting wikis and blogs. Offering broad coverage on all aspects of development for the...

IT Services Costs, Metrics, Benchmarking and Marketing
IT Services Costs, Metrics, Benchmarking and Marketing

IT Services is the first 100% customer-focused guide to satisfying the consumers of your company’s IT services -- and building the loyalty your IT organization needs. In this book, three leading IT professionals present a fully integrated, comprehensive approach to service delivery in today’s global, distributed environments.

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