Deep Learning dummies first edition – John Paul Mueller & Luca Massaron

When you talk to some people about deep learning, they think of some
deep dark mystery, but deep learning really isn’t a mystery at all — you
use it every time you talk to your smartphone, so you have it with you
every day. In fact, you find deep learning used everywhere. For example, you see it when using many applications online and even when you shop. You are surrounded by deep learning and don’t even realize it, which makes learning about deep learning essential because you can use it to do so much more than you might think possible.

Other people have another view of deep learning that has no basis in reality. They think that somehow deep learning will be responsible for some dire apocalypse, but that really isn’t possible with today’s technology. More likely is that someone will find a way to use deep learning to create fake people in order to commit crimes or to bilk the government out of thousands of dollars. However, killer robots are most definitely not part of the future.

Whether you’re part of the mystified crowd or the killer robot crowd, we hope that you’ll read Deep Learning For Dummies with the goal of understanding what deep learning can actually do. This technology can probably do a lot more in the way of mundane tasks than you think possible, but it also has limits, and you need to know about both.

Related posts:

Deep Learning with PyTorch - Vishnu Subramanian
Deep Learning with Hadoop - Dipayan Dev
Introduction to Machine Learning with Python - Andreas C.Muller & Sarah Guido
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
Amazon Machine Learning Developer Guild Version Latest
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Python Data Structures and Algorithms - Benjamin Baka
Neural Networks - A visual introduction for beginners - Michael Taylor
Java Deep Learning Essentials - Yusuke Sugomori
Coding Theory - Algorithms, Architectures and Application
Deep Learning and Neural Networks - Jeff Heaton
Data Science and Big Data Analytics - EMC Education Services
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
Python Deep Learning - Valentino Zocca & Gianmario Spacagna & Daniel Slater & Peter Roelants
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Introduction to Deep Learning Business Application for Developers - Armando Vieira & Bernardete Ribe...
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain
Python Machine Learning Eqution Reference - Sebastian Raschka
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Introduction to the Math of Neural Networks - Jeff Heaton
Deep Learning with Theano - Christopher Bourez
The hundred-page Machine Learning Book - Andriy Burkov
Deep Learning with Keras - Antonio Gulli & Sujit Pal
Pattern recognition and machine learning - Christopher M.Bishop
Fundamentals of Deep Learning - Nikhil Bubuma
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Deep Learning Illustrated - A visual, Interactive Guide to Arficial Intelligence First Edition - Jon...
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad