Grokking Deep Learning – MEAP v10 – Andrew W.Trask

It is a powerful tool for the incremental automation of intelligence.
From the beginning of time, humans have been building better and better tools to understand and control the environment around us. Deep Learning is today’s chapter in this story of innovation. Perhaps what makes this chapter so compelling is that this field is more of a mental innovation than a mechanical one. Much like its sister fields in Machine Learning, Deep Learning seeks to automate intelligence bit by bit, and in the past few years it has achieved enourmous success and progress in this endeavor, exceeding previous records in Computer Vision, Speech Recognition, Machine Translation, and many other tasks. This is particularly extraordinary given that Deep Learning seems to use largely the same brain- inspired algorithm (Neural Networks) for achieving these accomplishments across a vast number of fields. Even though Deep Learning is still an actively developing field with many challenges, recent developments have lead to tremendous excitement that perhaps we have in fact discovered more than just a great tool, but a window into our own minds as well.

Deep Learning has the potential for significant automation of skilled labor.
There is a substantial amount of hype around the potential impacts of Deep Learning if the current trend of progress is extrapolated at varying speeds. While many of these predictions are over-zealous, there is one that I think merits your consideration, job displacement. I think that this claim stands out from the rest for no other reason than if Deep Learning’s innovations stopped today, there would already be an incredible impact on skilled labor around the globe. Call center operators, taxi drivers, and low-level business analysts are compelling examples where Deep Learning can provide a low-cost alternative. Fortunately, the economy doesn’t turn on a dime, but in many ways we are already past the point of concern with the current power of the technology. It is my hope that you (and people you know) will be enabled by this book to transition from perhaps one of the industries facing disruption into an industry ripe with growth and prosperity, Deep Learning.

Related posts:

R Deep Learning Essentials - Dr. Joshua F.Wiley
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Deep Learning in Python - LazyProgrammer
Machine Learning with spark and python - Michael Bowles
TensorFlow for Deep Learning - Bharath Ramsundar & Reza Bosagh Zadeh
Introduction to the Math of Neural Networks - Jeff Heaton
Artificial Intelligence - A Very Short Introduction - Margaret A.Boden
Deep Learning and Neural Networks - Jeff Heaton
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Deep Learning with Python - Francois Chollet
Deep Learning with Theano - Christopher Bourez
Python Deep Learning Cookbook - Indra den Bakker
Data Science and Big Data Analytics - EMC Education Services
Foundations of Machine Learning second edition - Mehryar Mohri & Afshin Rostamizadeh & Ameet Talwalk...
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Introducing Data Science - Davy Cielen & Arno D.B.Meysman & Mohamed Ali
Python Machine Learning Cookbook - Practical solutions from preprocessing to Deep Learning - Chris A...
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Pattern recognition and machine learning - Christopher M.Bishop
Python 3 for Absolute Beginners - Tim Hall & J.P Stacey
Deep Learning with PyTorch - Vishnu Subramanian
Python Data Structures and Algorithms - Benjamin Baka
Artificial Intelligence - 101 things you must know today about our future - Lasse Rouhiainen
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster