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)

Storing your models

In order to be able to deploy your models to production, you need to be able to store a trained model on disk. CNTK offers two ways to store models on disk. You can either store checkpoints to continue training at a later time, or you can store a portable version of your model. Each of these storage methods has its own use.

Storing model checkpoints to continue training at a later point

Some models take a long time to train, sometimes up to weeks at a time. You don't want to lose all your progress when your machine crashes during training, or if there's a power outage.

This is where checkpointing becomes useful. You can create a checkpoint during training using a CheckpointConfig object. You...