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
Data Science and Big Data Analytics - EMC Education Services
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Deep Learning with PyTorch - Vishnu Subramanian
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Amazon Machine Learning Developer Guild Version Latest
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
Machine Learning with spark and python - Michael Bowles
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
Neural Networks - A visual introduction for beginners - Michael Taylor
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Python Deep Learning - Valentino Zocca & Gianmario Spacagna & Daniel Slater & Peter Roelants
Neural Networks and Deep Learning - Charu C.Aggarwal
An introduction to neural networks - Kevin Gurney & University of Sheffield
Deep Learning with Keras - Antonio Gulli & Sujit Pal
Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
Artificial Intelligence by example - Denis Rothman
Building Chatbots with Python Using Natural Language Processing and Machine Learning - Sumit Raj
Python Deep Learning Cookbook - Indra den Bakker
Deep Learning with Hadoop - Dipayan Dev
R Deep Learning Essentials - Dr. Joshua F.Wiley
Deep Learning with Python - Francois Chollet
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster
Fundamentals of Deep Learning - Nikhil Bubuma
Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
TensorFlow for Deep Learning - Bharath Ramsundar & Reza Bosagh Zadeh
