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:

Natural Language Processing in action - Hobson Lane & Cole Howard & Hannes Max Hapke
Intelligent Projects Using Python - Santanu Pattanayak
Data Science and Big Data Analytics - EMC Education Services
Deep Learning with PyTorch - Vishnu Subramanian
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Medical Image Segmentation Using Artificial Neural Networks
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Introduction to Machine Learning with Python - Andreas C.Muller & Sarah Guido
Fundamentals of Deep Learning - Nikhil Bubuma
Machine Learning - An Algorithmic Perspective second edition - Stephen Marsland
The hundred-page Machine Learning Book - Andriy Burkov
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
Deep Learning and Neural Networks - Jeff Heaton
Deep Learning dummies second edition - John Paul Mueller & Luca Massaronf
Python Data Structures and Algorithms - Benjamin Baka
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Deep Learning Illustrated - A visual, Interactive Guide to Arficial Intelligence First Edition - Jon...
Coding Theory - Algorithms, Architectures and Application
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
Python Machine Learning Eqution Reference - Sebastian Raschka
Artificial Intelligence - A Very Short Introduction - Margaret A.Boden
Pro Deep Learning with TensorFlow - Santunu Pattanayak
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Machine Learning - The art and science of alhorithms that make sense of data - Peter Flach
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
Introducing Data Science - Davy Cielen & Arno D.B.Meysman & Mohamed Ali
Python Machine Learning - Sebastian Raschka