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Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide

Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide

By : Meints
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Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide

Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide

By: 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)
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Deploying Models to Production

In the previous chapters of this book, we've worked on our skills for developing, testing, and using various deep learning models. We haven't talked much about the role of deep learning within the broader context of software engineering. In this last chapter, we will use the time to talk about continuous delivery, and the role of machine learning within this context. We will then look at how you can deploy models to production with a continuous delivery mindset. Finally, we will look at Azure Machine Learning service to properly manage the models you develop.

The following topics will be covered in this chapter:

  • Using machine learning in a DevOps environment
  • Storing models
  • Using Azure Machine Learning service to manage models
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