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
Building Chatbots with Python Using Natural Language Processing and Machine Learning - Sumit Raj
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Python Machine Learning Eqution Reference - Sebastian Raschka
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Fundamentals of Deep Learning - Nikhil Bubuma
Python Data Structures and Algorithms - Benjamin Baka
Deep Learning Illustrated - A visual, Interactive Guide to Arficial Intelligence First Edition - Jon...
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Deep Learning for Natural Language Processing - Jason Brownlee
Pattern recognition and machine learning - Christopher M.Bishop
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
The hundred-page Machine Learning Book - Andriy Burkov
Pro Deep Learning with TensorFlow - Santunu Pattanayak
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster
An introduction to neural networks - Kevin Gurney & University of Sheffield
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
TensorFlow for Deep Learning - Bharath Ramsundar & Reza Bosagh Zadeh
Coding Theory - Algorithms, Architectures and Application
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Deep Learning with Theano - Christopher Bourez
Introduction to Deep Learning Business Application for Developers - Armando Vieira & Bernardete Ribe...
Introduction to the Math of Neural Networks - Jeff Heaton
Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli
Python Deep Learning - Valentino Zocca & Gianmario Spacagna & Daniel Slater & Peter Roelants
Neural Networks - A visual introduction for beginners - Michael Taylor
Java Deep Learning Essentials - Yusuke Sugomori
Neural Networks and Deep Learning - Charu C.Aggarwal