Generative Deep Learning – Teaching Machines to Paint, Write, Compose and Play – David Foster

An undeniable part of the human condition is our ability to create. Since our earliest days as cave people, we have sought opportunities to generate original and beautiful creations. For early man, this took the form of cave paintings depicting wild animals and abstract patterns, created with pigments placed carefully and methodically onto rock. The Romantic Era gave us the mastery of Tchaikovsky symphonies, with their ability to inspire feelings of triumph and tragedy through sound waves, woven together to form beautiful melodies and harmonies. And in recent times, we have
found ourselves rushing to bookshops at midnight to buy stories about a fictional wizard, because the combination of letters creates a narrative that wills us to turn the page and find out what happens to our hero.

It is therefore not surprising that humanity has started to ask the ultimate question of creativity: can we create something that is in itself creative?
This is the question that generative modeling aims to answer. With recent advances in methodology and technology, we are now able to build machines that can paint origi‐nal artwork in a given style, write coherent paragraphs with long-term structure, compose music that is pleasant to listen to, and develop winning strategies for com‐plex games by generating imaginary future scenarios. This is just the start of a gener‐ative revolution that will leave us with no choice but to find answers to some of the biggest questions about the mechanics of creativity, and ultimately, what it means to be human. In short, there has never been a better time to learn about generative modeling—so let’s get started!

Related posts:

Deep Learning in Python - LazyProgrammer
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Amazon Machine Learning Developer Guild Version Latest
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Deep Learning with Python - A Hands-on Introduction - Nikhil Ketkar
Intelligent Projects Using Python - Santanu Pattanayak
Foundations of Machine Learning second edition - Mehryar Mohri & Afshin Rostamizadeh & Ameet Talwalk...
Deep Learning with Python - Francois Chollet
Python Deep Learning Cookbook - Indra den Bakker
Learn Keras for Deep Neural Networks - Jojo Moolayil
Deep Learning for Natural Language Processing - Jason Brownlee
Python 3 for Absolute Beginners - Tim Hall & J.P Stacey
Neural Networks - A visual introduction for beginners - Michael Taylor
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Introducing Data Science - Davy Cielen & Arno D.B.Meysman & Mohamed Ali
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
R Deep Learning Essentials - Dr. Joshua F.Wiley
Deep Learning - A Practitioner's Approach - Josh Patterson & Adam Gibson
Deep Learning Illustrated - A visual, Interactive Guide to Arficial Intelligence First Edition - Jon...
Deep Learning with Hadoop - Dipayan Dev
Introduction to the Math of Neural Networks - Jeff Heaton
Deep Learning with Theano - Christopher Bourez
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
Coding Theory - Algorithms, Architectures and Application
Hands-On Machine Learning with Scikit-Learn and TensorFlow - Aurelien Geron
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Introduction to Deep Learning - Eugene Charniak
Artificial Intelligence by example - Denis Rothman
Deep Learning with PyTorch - Vishnu Subramanian
Artificial Intelligence - 101 things you must know today about our future - Lasse Rouhiainen