Introduction to CNTK Succinctly (Microsoft Cognitive Toolkit)

Recommendation numbered : 13032020p1

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“Microsoft CNTK (Cognitive Toolkit, formerly Computational Network Toolkit), an open source code framework, enables you to create feed-forward neural network time series prediction systems, convolutional neural network image classifiers, and other deep learning systems. In Introduction to CNTK Succinctly, author James McCaffrey offers instruction on the basics of installing and running CNTK, and also addresses machine-learning regression and classification techniques. Exercises and explanations are included in each chapter”. (Syncfusion).


  • Getting Started
  • Logistic Regression
  • Fundamental Concepts
  • Neural Network Classifications
  • Neural Binary Classification
  • Neural Network Regression
  • LSTM Time Series Regression

“This e-book is based on CNTK version 2.3, released in late 2017. Because CNTK is still under active development, by the time you read this e-book, the latest version will likely be different. However, any changes will likely be relatively minor and consist mainly of additional functionality. In other words, the code presented here should work with any CNTK 2.x version”. (Chapter 1. Getting Started).

CNTK v2.7 Release Notes. (04/01/2019)


(Unofficial biography. For informational purposes only).

” James McCaffrey works for Microsoft Research in Redmond, Wash. He holds a B.A. in psychology from the University of California at Irvine, a B.A. in applied mathematics from California State University at Fullerton, an M.S. in information systems from Hawaii Pacific University, and a doctorate in cognitive psychology and computational statistics from the University of Southern California. James enjoys exploring all forms of activity that involve human interaction and combinatorial mathematics, such as the analysis of betting behavior associated with professional sports, machine learning algorithms, and data mining “. Source: []. Picture credits snapshot from[]. Personal blog: []

Please, thank the authors and the editor

Thank you very much for this work to @Syncfusion, and via @States_AI_IA #CNTK #Microsoft #ebook #free #openscience #openaccess #ai #artificialintelligence #ia #thebibleai #Toolkit #thanks

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