© 2019

Cognitive Computing Recipes

Artificial Intelligence Solutions Using Microsoft Cognitive Services and TensorFlow

  • Covers multiple paradigms including on-premise, in the cloud, and hybrid

  • Contains concise, hands-on, enterprise ready machine learning recipes for the uninitiated

  • Comprises both deep learning and machine learning, with examples using TensorFlow and CNTK


Table of contents

  1. Front Matter
    Pages i-xxvi
  2. Adnan Masood, Adnan Hashmi
    Pages 1-17
  3. Adnan Masood, Adnan Hashmi
    Pages 19-86
  4. Adnan Masood, Adnan Hashmi
    Pages 87-188
  5. Adnan Masood, Adnan Hashmi
    Pages 189-224
  6. Adnan Masood, Adnan Hashmi
    Pages 225-287
  7. Adnan Masood, Adnan Hashmi
    Pages 289-358
  8. Adnan Masood, Adnan Hashmi
    Pages 359-382
  9. Adnan Masood, Adnan Hashmi
    Pages 383-396
  10. Back Matter
    Pages 397-417

About this book


Solve your AI and machine learning problems using complete and real-world code examples. Using a problem-solution approach, this book makes deep learning and machine learning accessible to everyday developers, by providing a combination of tools such as cognitive services APIs, machine learning platforms, and libraries.

Along with an overview of the contemporary technology landscape, Machine Learning and Deep Learning with Cognitive Computing Recipes covers the business case for machine learning and deep learning. Covering topics such as digital assistants, computer vision, text analytics, speech, and robotics process automation this book offers a comprehensive toolkit that you can apply quickly and easily in your own projects. With its focus on Microsoft Cognitive Services offerings, you’ll see recipes using multiple different environments including TensowFlow and CNTK to give you a broader perspective of the deep learning ecosystem. 

You will:
  • Build production-ready solutions using Microsoft Cognitive Services APIs
  • Apply deep learning using TensorFlow and Microsoft Cognitive Toolkit (CNTK)
  • Solve enterprise problems in natural language processing and computer vision 
  • Discover the machine learning development life cycle – from formal problem definition to deployment at scale


Machine Learning Deep Learning Cognitive Computing TensorFlow Microsoft Cognitive Toolkit Artificial Intelligence Text Analytics Natural Language Processing Knowledge Management

Authors and affiliations

  1. 1.StanfordUSA
  2. 2.NashvilleUSA

About the authors

Adnan Masood, Ph.D. is an artificial intelligence and machine learning researcher, software architect, and Microsoft MVP (Most Valuable Professional) for Data Platform. He currently works at UST Global as Chief Architect of AI and Machine Learning, where he collaborates with Stanford Artificial Intelligence Lab, and MIT AI Lab for building enterprise solutions.

Author of Amazon bestseller in programming languages, Functional Programming with F#, Dr. Masood teaches data science at Park University, and has taught Windows Communication Foundation (WCF) courses at the University of California, San Diego. He is a regular speaker to various academic and technology conferences (WICT, DevIntersection, IEEE-HST, IASA, and DevConnections), local code camps, and user groups. He also volunteers as STEM (Science Technology, Engineering and Math) robotics coach for elementary and middle school students. 

Adnan Hashmi has 20 years’ experience in the technology industry working with a host of clients in healthcare, finance, construction, and consulting. He currently works at Microsoft data and AI space, engaging with financial services clients. He holds a Master’s degree in software engineering from the Shaheed Zulfikar Ali Bhutto Institute of Science & Technology (SZABIST), Karachi, Pakistan, and is passionate about machine learning, music, and education.

Bibliographic information

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