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:

Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
Data Science and Big Data Analytics - EMC Education Services
Deep Learning Illustrated - A visual, Interactive Guide to Arficial Intelligence First Edition - Jon...
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Artificial Intelligence - A Very Short Introduction - Margaret A.Boden
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Medical Image Segmentation Using Artificial Neural Networks
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Python Deep Learning - Valentino Zocca & Gianmario Spacagna & Daniel Slater & Peter Roelants
Building Chatbots with Python Using Natural Language Processing and Machine Learning - Sumit Raj
R Deep Learning Essentials - Dr. Joshua F.Wiley
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Foundations of Machine Learning second edition - Mehryar Mohri & Afshin Rostamizadeh & Ameet Talwalk...
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Python Machine Learning - Sebastian Raschka
Java Deep Learning Essentials - Yusuke Sugomori
Deep Learning for Natural Language Processing - Jason Brownlee
Python Machine Learning Eqution Reference - Sebastian Raschka
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Python Machine Learning Cookbook - Practical solutions from preprocessing to Deep Learning - Chris A...
Deep Learning in Python - LazyProgrammer
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Introduction to Deep Learning Business Application for Developers - Armando Vieira & Bernardete Ribe...
Deep Learning with Hadoop - Dipayan Dev
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Deep Learning dummies second edition - John Paul Mueller & Luca Massaronf
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron