Biologists, too, have used AI—in the form of ‘artificial life’ (A-Life), which develops computer models of differing aspects of living organisms. This helps them to explain various types of animal behaviour, the development of bodily form, biological evolution, and the nature of life itself. Besides affecting the life sciences, AI has influenced philosophy. Many philosophers today base their accounts of mind on AI concepts. They use these to address, for instance, the notorious mind–body problem, the conundrum of free will, and the many puzzles regarding consciousness. However, these philosophical ideas are hugely controversial. And there are deep disagreements about whether any AI system could possess real intelligence, creativity, or life. Last, but not least, AI has challenged the ways in which we think about humanity—and its future. Indeed, some people worry about whether we actually have a future, because they foresee AI surpassing human intelligence across the board. Although a few thinkers welcome this prospect, most dread it: what place will remain, they ask, for human dignity and esponsibility?
Artificial Intelligence – A Very Short Introduction – Margaret A.Boden
Learn Keras for Deep Neural Networks - Jojo Moolayil
Data Science and Big Data Analytics - EMC Education Services
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Artificial Intelligence - 101 things you must know today about our future - Lasse Rouhiainen
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Introduction to the Math of Neural Networks - Jeff Heaton
Python Machine Learning - Sebastian Raschka
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster
Amazon Machine Learning Developer Guild Version Latest
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
Python 3 for Absolute Beginners - Tim Hall & J.P Stacey
Deep Learning for Natural Language Processing - Jason Brownlee
Introduction to Deep Learning Business Application for Developers - Armando Vieira & Bernardete Ribe...
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Introduction to Scientific Programming with Python - Joakim Sundnes
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain
Neural Networks - A visual introduction for beginners - Michael Taylor
Pattern recognition and machine learning - Christopher M.Bishop
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
Machine Learning - An Algorithmic Perspective second edition - Stephen Marsland
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Deep Learning with Keras - Antonio Gulli & Sujit Pal
Deep Learning with Theano - Christopher Bourez
Machine Learning Mastery with Python - Understand your data, create accurate models and work project...
Introduction to Machine Learning with Python - Andreas C.Muller & Sarah Guido