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
Deep Learning with Python - Francois Cholletf
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Deep Learning with Python - Francois Chollet
TensorFlow for Deep Learning - Bharath Ramsundar & Reza Bosagh Zadeh
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Data Science and Big Data Analytics - EMC Education Services
An introduction to neural networks - Kevin Gurney & University of Sheffield
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Machine Learning - An Algorithmic Perspective second edition - Stephen Marsland
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Pattern recognition and machine learning - Christopher M.Bishop
Deep Learning with Theano - Christopher Bourez
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster
Amazon Machine Learning Developer Guild Version Latest
The hundred-page Machine Learning Book - Andriy Burkov
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Introduction to Scientific Programming with Python - Joakim Sundnes
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Learn Keras for Deep Neural Networks - Jojo Moolayil
Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli
Python Deep Learning - Valentino Zocca & Gianmario Spacagna & Daniel Slater & Peter Roelants
Pro Deep Learning with TensorFlow - Santunu Pattanayak
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
Deep Learning with PyTorch - Vishnu Subramanian
Python 3 for Absolute Beginners - Tim Hall & J.P Stacey
Deep Learning and Neural Networks - Jeff Heaton
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
Coding Theory - Algorithms, Architectures and Application