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 Deep Learning Cookbook - Indra den Bakker
Introduction to the Math of Neural Networks - Jeff Heaton
Pro Deep Learning with TensorFlow - Santunu Pattanayak
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
Python Machine Learning - Sebastian Raschka
Introducing Data Science - Davy Cielen & Arno D.B.Meysman & Mohamed Ali
Deep Learning in Python - LazyProgrammer
Machine Learning Mastery with Python - Understand your data, create accurate models and work project...
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Python Deep Learning - Valentino Zocca & Gianmario Spacagna & Daniel Slater & Peter Roelants
Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Python 3 for Absolute Beginners - Tim Hall & J.P Stacey
Python Machine Learning Cookbook - Practical solutions from preprocessing to Deep Learning - Chris A...
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
Python Data Structures and Algorithms - Benjamin Baka
TensorFlow for Deep Learning - Bharath Ramsundar & Reza Bosagh Zadeh
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
The hundred-page Machine Learning Book - Andriy Burkov
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Artificial Intelligence - 101 things you must know today about our future - Lasse Rouhiainen
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Fundamentals of Deep Learning - Nikhil Bubuma
Machine Learning with spark and python - Michael Bowles
Introduction to Deep Learning Business Application for Developers - Armando Vieira & Bernardete Ribe...
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
Deep Learning with Theano - Christopher Bourez
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Neural Networks and Deep Learning - Charu C.Aggarwal
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster