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
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Data Science and Big Data Analytics - EMC Education Services
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Medical Image Segmentation Using Artificial Neural Networks
Deep Learning in Python - LazyProgrammer
Artificial Intelligence by example - Denis Rothman
Building Chatbots with Python Using Natural Language Processing and Machine Learning - Sumit Raj
Deep Learning with Theano - Christopher Bourez
Deep Learning with PyTorch - Vishnu Subramanian
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
Amazon Machine Learning Developer Guild Version Latest
Pattern recognition and machine learning - Christopher M.Bishop
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Deep Learning for Natural Language Processing - Jason Brownlee
An introduction to neural networks - Kevin Gurney & University of Sheffield
The hundred-page Machine Learning Book - Andriy Burkov
Python Machine Learning Cookbook - Practical solutions from preprocessing to Deep Learning - Chris A...
Machine Learning Mastery with Python - Understand your data, create accurate models and work project...
Python Machine Learning Eqution Reference - Sebastian Raschka
TensorFlow for Deep Learning - Bharath Ramsundar & Reza Bosagh Zadeh
Machine Learning - An Algorithmic Perspective second edition - Stephen Marsland
R Deep Learning Essentials - Dr. Joshua F.Wiley
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Deep Learning dummies second edition - John Paul Mueller & Luca Massaronf
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Fundamentals of Deep Learning - Nikhil Bubuma
Deep Learning and Neural Networks - Jeff Heaton
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Introduction to Deep Learning - Eugene Charniak
Introduction to Machine Learning with Python - Andreas C.Muller & Sarah Guido
