Neural Networks – A visual introduction for beginners – Michael Taylor

Thi s book is designed as a visual introducti on to neural networks. It is for BEGINNERS and those who have minimal knowledge of the topic. If you al ready have a general understanding, you might not get much out of this book. You don’t need to read front to back. Skip around to what you find the most helpful or is perking your interest. We’ve included lots of links throughout the book to make this easy. Just click on them. We slowly layer in new terminology and concepts each chapter. This means that i f you jump to chapter 4 without having read chapter 3, you might come across terminology that you do not understand. Be aware of this, and remember: you can always jump back to clarify a topic or concept.

Related posts:

Python Data Structures and Algorithms - Benjamin Baka
Deep Learning for Natural Language Processing - Jason Brownlee
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
Neural Networks and Deep Learning - Charu C.Aggarwal
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Fundamentals of Deep Learning - Nikhil Bubuma
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
R Deep Learning Essentials - Dr. Joshua F.Wiley
Artificial Intelligence - 101 things you must know today about our future - Lasse Rouhiainen
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Scikit-learn Cookbook Second Edition over 80 recipes for machine learning - Julian Avila & Trent Hau...
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Machine Learning - An Algorithmic Perspective second edition - Stephen Marsland
An introduction to neural networks - Kevin Gurney & University of Sheffield
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Pro Deep Learning with TensorFlow - Santunu Pattanayak
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli
Deep Learning with Python - Francois Chollet
Python Machine Learning - Sebastian Raschka
Introduction to Deep Learning - Eugene Charniak
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain
Machine Learning - A Probabilistic Perspective - Kevin P.Murphy
Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
Artificial Intelligence by example - Denis Rothman
Generative Deep Learning - Teaching Machines to Paint, Write, Compose and Play - David Foster