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 PyTorch - Vishnu Subramanian
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
Fundamentals of Deep Learning - Nikhil Bubuma
Building Chatbots with Python Using Natural Language Processing and Machine Learning - Sumit Raj
Amazon Machine Learning Developer Guild Version Latest
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Machine Learning with spark and python - Michael Bowles
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Data Science and Big Data Analytics - EMC Education Services
TensorFlow for Deep Learning - Bharath Ramsundar & Reza Bosagh Zadeh
Introduction to Deep Learning - Eugene Charniak
Coding Theory - Algorithms, Architectures and Application
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
Learn Keras for Deep Neural Networks - Jojo Moolayil
Python Data Structures and Algorithms - Benjamin Baka
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Foundations of Machine Learning second edition - Mehryar Mohri & Afshin Rostamizadeh & Ameet Talwalk...
Introduction to Deep Learning Business Application for Developers - Armando Vieira & Bernardete Ribe...
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Pattern recognition and machine learning - Christopher M.Bishop
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
