Deep Learning with C#, .Net and Kelp.Net Digital Back Issue Cover

Deep Learning with C#, .Net and Kelp.Net Magazine (Digital)

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

Get hands on with Kelp.Net, Microsoft’s latest Deep Learning framework 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 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. What will you 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 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. Table of Contents 1. Introduction 2. ML/DL Terms and Concepts 3. Deep Instrumentation 4. Kelp.Net Reference 5. Loading and Saving Models 6. Model Testing and Training 7. Sample Deep Learning Tests 8. Creating Your Own Deep Learning Tests 9. Appendix A: Evaluation Metrics 10. Appendix B: OpenCL About the Author Matt R. Cole is a seasoned developer and published author with over 30 years’ experience in Microsoft Windows, C, C++, C# and .Net. He is the owner of Evolved AI Solutions, a premier provider of advanced Machine Learning/Bio-AI technologies. He developed the first enterprise grade MicroService framework written completely in C# and .Net, which is used in production by a major hedge fund in NYC. He also developed the first Bio Artificial Intelligence framework which completely integrates mirror and canonical neurons. He continues to push the limits of Machine Learning, Biological Artificial Intelligence, Deep Learning and MicroServices. In his spare time Matt loves to continue his education and contribute to open source efforts such as Kelp.Net. His Website: www.evolvedaisolutions.com His LinkedIn Profile: www.linkedin.com/in/evolvedai/ His Blog: www.evolvedaisolutions.com/blog.html


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