Artificial Intelligence by example – Denis Rothman

This book will take you through all of the main aspects of artificial intelligence:

  • The theory of machine learning and deep learning
  • Mathematical representations of the main AI algorithms
  • Real life case studies
  • Tens of opensource Python programs using TensorFlow, TensorBoard, Keras and more
  • Cloud AI Platforms: Google, Amazon Web Services, IBM Watson and IBM Q to introduce you to quantum computing
  • An Ubuntu VM containing all the opensource programs that you can run in one-click
  • Online videos

This book will take you to the cutting edge and beyond with innovations that show how to improve existing solutions to make you a key asset as a consultant, developer, professor or any person involved in artificial intelligence.

Who this book is for

  • This book contains the main artificial intelligence algorithms on the market today. Each machine learning and deep learning solution is illustrated by a case study and an open source program available on GitHub.
  • Project managers and consultants: To understand how to manage AI input datasets, make a solution choice (cloud platform or development), and use the outputs of an AI system.
  • Teachers, students, and developers: This book provides an overview of many key AI components, with tens of Python sample programs that run on Windows and Linux. A VM is available as well.
  • Anybody who wants to understand how AI systems are built and what they are used for.

Related posts:

Intelligent Projects Using Python - Santanu Pattanayak
Neural Networks - A visual introduction for beginners - Michael Taylor
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Python Deep Learning Cookbook - Indra den Bakker
Introducing Data Science - Davy Cielen & Arno D.B.Meysman & Mohamed Ali
Machine Learning - An Algorithmic Perspective second edition - Stephen Marsland
Deep Learning with Python - Francois Chollet
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Python 3 for Absolute Beginners - Tim Hall & J.P Stacey
Introduction to the Math of Neural Networks - Jeff Heaton
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain
Artificial Intelligence - A Very Short Introduction - Margaret A.Boden
Artificial Intelligence - 101 things you must know today about our future - Lasse Rouhiainen
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Deep Learning Illustrated - A visual, Interactive Guide to Arficial Intelligence First Edition - Jon...
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Introduction to Scientific Programming with Python - Joakim Sundnes
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Learn Keras for Deep Neural Networks - Jojo Moolayil
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Fundamentals of Deep Learning - Nikhil Bubuma
Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Deep Learning with Keras - Antonio Gulli & Sujit Pal
Pattern recognition and machine learning - Christopher M.Bishop
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Deep Learning dummies second edition - John Paul Mueller & Luca Massaronf
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili