Book Image

Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide

By : Willem Meints
Book Image

Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide

By: Willem Meints

Overview of this book

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
Table of Contents (9 chapters)

To get the most out of this book

We recommend you have experience with Python 3 so that you know what the syntax looks like. You will need to run either Linux or Windows on a machine with a decent amount of memory and CPU power, as the samples in this book can take a long time to run on an older machine. If you are lucky enough to have a gaming graphics card in your machine from NVIDIA, we definitely recommend looking at the instructions on how to install the GPU version of CNTK, as this can speed up the samples by quite a large factor. Some sections in the book assume that you know a little bit about Java or C#. Although not required, it is useful to have a basic understanding of the syntax of one or more of these languages.

Download the example code files

You can download the example code files for this book from your account at If you purchased this book elsewhere, you can visit and register to have the files emailed directly to you.

You can download the code files by following these steps:

  1. Log in or register at
  2. Select the SUPPORT tab.
  3. Click on Code Downloads & Errata.
  4. Enter the name of the book in the Search box and follow the onscreen instructions.

Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:

  • WinRAR/7-Zip for Windows
  • Zipeg/iZip/UnRarX for Mac
  • 7-Zip/PeaZip for Linux

The code bundle for the book is also hosted on GitHub at In case there's an update to the code, it will be updated on the existing GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at Check them out!

Code in Action

Conventions used

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "We use the StreamDef class for this purpose".

A block of code is set as follows:

from cntk.layers import Dense
from cntk import input_variable

features = input_variable(50)
layer = Dense(50)(features)

Any command-line input or output is written as follows:

cd ch2
jupyter notebook

Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "To create a new instance of this resource type, click the create button."

Warnings or important notes appear like this.
Tips and tricks appear like this.