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
Deep Learning with Keras - Antonio Gulli & Sujit Pal
Python Machine Learning - Sebastian Raschka
Deep Learning with Theano - Christopher Bourez
Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Introduction to Machine Learning with Python - Andreas C.Muller & Sarah Guido
Python Deep Learning Cookbook - Indra den Bakker
Deep Learning in Python - LazyProgrammer
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Coding Theory - Algorithms, Architectures and Application
Foundations of Machine Learning second edition - Mehryar Mohri & Afshin Rostamizadeh & Ameet Talwalk...
An introduction to neural networks - Kevin Gurney & University of Sheffield
Introduction to the Math of Neural Networks - Jeff Heaton
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
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
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain
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Medical Image Segmentation Using Artificial Neural Networks
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Machine Learning with Python for everyone - Mark E.Fenner