Willem Meints - Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide: A practical guide to building neural networks using Microsofts open source deep learning framework
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- Book:Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide: A practical guide to building neural networks using Microsofts open source deep learning framework
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Learn how to train popular deep learning architectures such as autoencoders, convolutional and recurrent neural networks while discovering how you can use deep learning models in your software applications with Microsoft Cognitive Toolkit
Key Features
- Train different types of neural networks using Cognitive Toolkit and deploy it to production
- Evaluate the performance of your models and improve your deep learning skills
Book Description
Cognitive Toolkit is a very popular and recently open sourced deep learning toolkit by Microsoft. Cognitive Toolkit is used to train fast and effective deep learning models. This book will be a quick introduction to using Cognitive Toolkit and will teach you how to train and validate different types of neural networks, such as convolutional and recurrent neural networks.
This book will help you understand the basics of deep learning. You will learn how to use Microsoft Cognitive Toolkit to build deep learning models and discover what makes this framework unique so that you know when to use it. This book will be a quick, no-nonsense introduction to the library and will teach you how to train different types of neural networks, such as convolutional neural networks, recurrent neural networks, autoencoders, and more, using Cognitive Toolkit. Then we will look at two scenarios in which deep learning can be used to enhance human capabilities. The book will also demonstrate how to evaluate your models performance to ensure it trains and runs smoothly and gives you the most accurate results. Finally, you will get a short overview of how Cognitive Toolkit fits in to a DevOps environment
What you will learn
- Set up your deep learning environment for the Cognitive Toolkit on Windows and Linux
- Pre-process and feed your data into neural networks
- Use neural networks to make effcient predictions and recommendations
- Train and deploy effcient neural networks such as CNN and RNN
- Detect problems in your neural network using TensorBoard
- Integrate Cognitive Toolkit with Azure ML Services for effective deep learning
Who this book is for
Data Scientists, Machine learning developers, AI developers who wish to train and deploy effective deep learning models using Microsoft CNTK will find this book to be useful. Readers need to have experience in Python or similar object-oriented language like C# or Java.
Willem Meints: author's other books
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Copyright 2019 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
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Acquisition Editor: Siddharth Mandal
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First published: March 2019
Production reference: 1260319
Published by Packt Publishing Ltd.
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ISBN 978-1-78980-299-3
www.packtpub.com
To my wife she always makes me smile, no matter where we are.
To my two little neural networks, also known as my sons, Tom and Luuk.
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Willem Meints is a software architect and engineer with a wide variety of interests. His background in software engineering hasn't stopped him from exploring new areas, such as machine learning, as part of his daily work. This sparked a deep passion for everything related to artificial intelligence and deep learning.
Willem studied electronics after his high school career, but quickly discovered he had more fun building applications. This led to his decision to leave the world of electronics and launch a career in software engineering. After he finished his bachelor's degree in software engineering, he started working for Info Support, where he's been working ever since.
Bahrudin Hrnjica holds a PhD in technical science from the University of Biha. Currently, he is assistant professor at the university, teaching students in the fields of numerical analysis, mathematical modeling, and machine learning. Besides teaching at the university, he has many years' experience in the software industry, working on custom solutions based on cloud technologies, machine learning, .NET, and Visual Studio. As an expert in development technologies, Microsoft recognized him as Microsoft Most Valuable Professional (Microsoft MVP) for the first time in 2011. He is an author of several books, online articles, and open source projects, as well as having spoken at many local and regional conferences, code camps, and workshops.
If you're interested in becoming an author for Packt, please visit authors.packtpub.com and apply today. We have worked with thousands of developers and tech professionals, just like you, to help them share their insight with the global tech community. You can make a general application, apply for a specific hot topic that we are recruiting an author for, or submit your own idea.
Artificial intelligence (AI) is here to enhance humans by automating some of the tasks we do every day, so we can spend more time fully realizing our potential. We've been using software programs as tools to automate many of the simpler tasks. Now it is time to take on the challenge of automating more complicated tasks.
There's a lot happening in the area of AI and more people than ever are looking to expand their existing toolkit with new techniques to make their software smarter. Machine learning, and especially deep learning, are highly important tools with which we can enhance what we are already doing with our computers.
This book aims to help you get to grips with one of the most popular deep learning tools, CNTK. We will look at what this relatively young open source deep learning framework offers. At the end of this book, you'll have a solid understanding of the framework and some of the scenarios in which it can be used.
This book is great for developers with some experience in Java, C#, or Python. We're assuming you're pretty new to machine learning. However, this book is also great for people who have worked with other deep learning frameworks before and want to learn another great deep learning tool.
, Getting Started with CNTK , introduces you to the CNTK framework and the world of deep learning. It explains how to install the tools on your computer and how to use a GPU with CNTK.
, Building Neural Networks with CNTK , explains how to build your first neural network with CNTK. We dive into the basic building blocks and see how to train a neural network with CNTK.
, Getting Data into Your Neural Network , shows you different methods of loading data for training neural networks. You'll learn how to work with both small datasets, and datasets that don't fit in your computer's memory.
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