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
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
An introduction to neural networks - Kevin Gurney & University of Sheffield
Deep Learning dummies second edition - John Paul Mueller & Luca Massaronf
Deep Learning with PyTorch - Vishnu Subramanian
Pattern recognition and machine learning - Christopher M.Bishop
Medical Image Segmentation Using Artificial Neural Networks
Machine Learning with spark and python - Michael Bowles
Deep Learning with Python - Francois Chollet
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Deep Learning Illustrated - A visual, Interactive Guide to Arficial Intelligence First Edition - Jon...
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Deep Learning with Hadoop - Dipayan Dev
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Artificial Intelligence - A Very Short Introduction - Margaret A.Boden
Introduction to Deep Learning - Eugene Charniak
Deep Learning for Natural Language Processing - Jason Brownlee
Foundations of Machine Learning second edition - Mehryar Mohri & Afshin Rostamizadeh & Ameet Talwalk...
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
Artificial Intelligence by example - Denis Rothman
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Machine Learning with Python for everyone - Mark E.Fenner
TensorFlow for Deep Learning - Bharath Ramsundar & Reza Bosagh Zadeh
Data Science and Big Data Analytics - EMC Education Services
Coding Theory - Algorithms, Architectures and Application
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman