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
Python Deep Learning - Valentino Zocca & Gianmario Spacagna & Daniel Slater & Peter Roelants
Coding Theory - Algorithms, Architectures and Application
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Deep Learning with PyTorch - Vishnu Subramanian
Python Machine Learning Eqution Reference - Sebastian Raschka
Deep Learning Illustrated - A visual, Interactive Guide to Arficial Intelligence First Edition - Jon...
Python Deep Learning Cookbook - Indra den Bakker
Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
Medical Image Segmentation Using Artificial Neural Networks
Machine Learning with spark and python - Michael Bowles
Deep Learning with Theano - Christopher Bourez
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
Introduction to Deep Learning - Eugene Charniak
Neural Networks and Deep Learning - Charu C.Aggarwal
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Machine Learning - An Algorithmic Perspective second edition - Stephen Marsland
Introduction to Scientific Programming with Python - Joakim Sundnes
Deep Learning with Keras - Antonio Gulli & Sujit Pal
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Deep Learning for Natural Language Processing - Jason Brownlee
Introducing Data Science - Davy Cielen & Arno D.B.Meysman & Mohamed Ali
Deep Learning with Hadoop - Dipayan Dev
An introduction to neural networks - Kevin Gurney & University of Sheffield
TensorFlow for Deep Learning - Bharath Ramsundar & Reza Bosagh Zadeh
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Introduction to Machine Learning with Python - Andreas C.Muller & Sarah Guido
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Java Deep Learning Essentials - Yusuke Sugomori