Did you know that artificial intelligence (AI) is changing our world faster than we can imagine? Try to envision all the mind-boggling benefits of a world where AI can help us to enjoy almost every area of our lives. This world will be a reality in the very near future, but along with the benefits will come new challenges as well. AI will impact every area of our lives, in some ways that we can’t even predict, whether we like it or not. Would you like to know more about this fascinating technology? In this non-technical guidebook, you will discover the many ways in which AI is already changing our world, and how you can adjust to these changes. You will also learn practical methods you can use to apply AI in your own personal and professional life. Artificial intelligence will help us to do almost everything better, faster and cheaper, but it will also bring about some considerable challenges that we need to start preparing for now. One common misconception is that only big technology companies can work with and benefit from AI. In this book you will discover several creative ways in which you can do the same.
Artificial Intelligence – 101 things you must know today about our future – Lasse Rouhiainen
Foundations of Machine Learning second edition - Mehryar Mohri & Afshin Rostamizadeh & Ameet Talwalk...
Introduction to Deep Learning - Eugene Charniak
Building Chatbots with Python Using Natural Language Processing and Machine Learning - Sumit Raj
Python Machine Learning Eqution Reference - Sebastian Raschka
Neural Networks - A visual introduction for beginners - Michael Taylor
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
TensorFlow for Deep Learning - Bharath Ramsundar & Reza Bosagh Zadeh
Introduction to Deep Learning Business Application for Developers - Armando Vieira & Bernardete Ribe...
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Machine Learning - An Algorithmic Perspective second edition - Stephen Marsland
Data Science and Big Data Analytics - EMC Education Services
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Python Machine Learning Cookbook - Practical solutions from preprocessing to Deep Learning - Chris A...
Deep Learning with Python - Francois Cholletf
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
Pattern recognition and machine learning - Christopher M.Bishop
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Coding Theory - Algorithms, Architectures and Application
Artificial Intelligence by example - Denis Rothman
Deep Learning in Python - LazyProgrammer
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
The hundred-page Machine Learning Book - Andriy Burkov
Deep Learning and Neural Networks - Jeff Heaton
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron