Deep Learning with C#, .Net and Kelp.Net

Deep Learning with C#, .Net and Kelp.Net
Author :
Publisher : BPB Publications
Total Pages : 392
Release :
ISBN-10 : 9789388511018
ISBN-13 : 9388511018
Rating : 4/5 (018 Downloads)

Book Synopsis Deep Learning with C#, .Net and Kelp.Net by : Matt R. Cole

Download or read book Deep Learning with C#, .Net and Kelp.Net written by Matt R. Cole and published by BPB Publications. This book was released on 2019-05-14 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get hands on with Kelp.Net , MicrosoftÕs latest Deep Learning framework Description Deep Learning with Kelp.Net is the ultimate reference for C# .Net developers who are passionate about deep learning. Readers will learn all the skills necessary to develop powerful, scalable and flexible deep learning models from a fluid and easy to use API. Upon completing the book the reader will have all the tools necessary to add powerful deep learning capabilities to their new or existing applications. Key Features Deep Learning Basics The ultimate Kelp.Net reference guide Develop state of the art deep learning applications C# Deep Learning code Develop advanced deep learning models with minimal code Develop your own advanced Deep Learning models Loading and Saving Deep Learning Models Comprehensive Kelp.Net reference Sample Deep Learning Models and Tests OpenCL Reference Easily add deep learning to your applications Many sample models and tests Intuitive and user friendly What you will learn In-depth knowledge of Kelp.Net How to develop Deep Learning models C# Deep Learning programming Open-Computing Language (OpenCL) Loading and saving Deep Learning models How to develop and use activation functions How to test Deep Learning models Who This Book is For This book targets C# .Net developers who are passionate about deep learning yet want to do so from an easy and intuitive API. Table of Contents Introduction ML/DL Terms and Concepts Deep Instrumentation Kelp.Net Reference Loading and Saving Models Model Testing and Training Sample Deep Learning Tests Creating Your Own Deep Learning Tests Appendix A: Evaluation Metrics Appendix B: OpenCL


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