Artificial Intelligence By Example
eBook - ePub

Artificial Intelligence By Example

Develop machine intelligence from scratch using real artificial intelligence use cases

Denis Rothman

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  1. 490 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Artificial Intelligence By Example

Develop machine intelligence from scratch using real artificial intelligence use cases

Denis Rothman

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About This Book

Publisher's Note: This edition from 2018 is outdated! A new second edition, completely updated for Python 3.x and its latest libraries, and TensorFlow 2.x, is now available. It features new and more practical examples executed on various platforms like TensorBoard, IBMQ, Google Dialogflow, Quirk, and more.

Key Features

  • AI-based examples to guide you in designing and implementing machine intelligence
  • Develop your own method for future AI solutions
  • Acquire advanced AI, machine learning, and deep learning design skills

Book Description

Artificial intelligence has the potential to replicate humans in every field. Artificial Intelligence By Example serves as a starting point for you to understand how AI is built, with the help of intriguing examples and case studies.

Artificial Intelligence By Example will make you an adaptive thinker and help you apply concepts to real-life scenarios. Using some of the most interesting AI examples, right from a simple chess engine to a cognitive chatbot, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and IoT, and develop emotional quotient in chatbots using neural networks.

You will move on to designing AI solutions in a simple manner rather than get confused by complex architectures and techniques. This comprehensive guide will be a starter kit for you to develop AI applications on your own.

By the end of this book, you will have understood the fundamentals of AI and worked through a number of case studies that will help you develop your business vision.

What you will learn

  • Use adaptive thinking to solve real-life AI case studies
  • Rise beyond being a modern-day factory code worker
  • Acquire advanced AI, machine learning, and deep learning designing skills
  • Learn about cognitive NLP chatbots, quantum computing, and IoT and blockchain technology
  • Understand future AI solutions and adapt quickly to them
  • Develop out-of-the-box thinking to face any challenge the market presents

Who this book is for

Artificial Intelligence by Example is a simple, explanatory, and descriptive guide for junior developers, experienced developers, technology consultants, and those interested in AI who want to understand the fundamentals of artificial intelligence and implement it practically by devising smart solutions. Prior experience with Python and statistical knowledge is essential to make the most out of this book.

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Contributors

About the author

Denis Rothman graduated from l'Université Paris-Sorbonne and l'Université Paris-Diderot, writing one of the very first word2matrix embedding solutions. He began his career authoring one of the first AI cognitive NLP chatbots applied as a language teacher for Moët et Chandon and other companies. He authored an AI resource optimizer for IBM and apparel producers. He then authored an Advanced Planning and Scheduling (APS) solution used worldwide.
I want to thank the corporations who trusted me from the start to deliver artificial intelligence solutions and share the risks of continuous innovation. I also thank my family, who believed I would make it big at all times.

About the reviewers

Armando Fandango creates AI-powered products by leveraging his expertise in deep learning, machine learning, distributed computing, and computational methods. He advises Owen.ai Inc., Real Engagement, and Loyalty Inc. on AI product strategy. He founded NeuraSights to create insights using neural networks. He was the chief data scientist and CTO for Epic Engg., Consulting Group LLC, and director of data science for Sonobi. He has advised high-tech startups as an AI expert and advisory board member.
Nicolas Guet is a financial controller at GRDF. He was a project leader for ENGIE and a SAP BI consultant for Capgemini.
He graduated from Université Pierre et Marie Curie (Paris VI) and Université Paris Sud (Paris XI). He also designed a decision-making tool in Java that was part of an AI Advanced Planning System, managing hundreds of thousands of orders for 100+ suppliers worldwide. He is dedicated to promoting sustainable energy and smart grids.
Jérémie Rothman is an IT project manager at the French National Forest Office (ONF). He was an IT consultant for TCS France and ...

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