In 2006, Geoffrey Hinton et al. published a paper showing how to train a deep neural network capable of recognizing handwritten digits with state-of-the-art precision (>98%). They branded this technique “Deep Learning.” Training a deep neural net was widely considered impossible at the time,
21 and most researchers had abandoned the idea since the 1990s. This paper revived the interest of the scientific community and before long many new papers demonstrated that Deep Learning was not only
possible, but capable of mind-blowing achievements that no other Machine Learning (ML) technique could hope to match (with the help of tremendous computing power and great amounts of data). This enthusiasm soon extended to many other areas of Machine Learning. Fast-forward 10 years and Machine Learning has conquered the industry: it is now at the heart of much of the magic in today’s high-tech products, ranking your web search results, powering your smartphone’s speech recognition, recommending vid‐eos, and beating the world champion at the game of Go. Before you know it, it will be driving your car.
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Java Deep Learning Essentials - Yusuke Sugomori
Building Chatbots with Python Using Natural Language Processing and Machine Learning - Sumit Raj
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Python 3 for Absolute Beginners - Tim Hall & J.P Stacey
Data Science and Big Data Analytics - EMC Education Services
Medical Image Segmentation Using Artificial Neural Networks
Artificial Intelligence - A Very Short Introduction - Margaret A.Boden
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Python Machine Learning - Sebastian Raschka
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Neural Networks - A visual introduction for beginners - Michael Taylor
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
Machine Learning with spark and python - Michael Bowles
Introducing Data Science - Davy Cielen & Arno D.B.Meysman & Mohamed Ali
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Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
The hundred-page Machine Learning Book - Andriy Burkov
Deep Learning with Python - Francois Chollet
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
TensorFlow for Deep Learning - Bharath Ramsundar & Reza Bosagh Zadeh
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Python Deep Learning Cookbook - Indra den Bakker
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Introduction to Machine Learning with Python - Andreas C.Muller & Sarah Guido
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Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain