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:

The hundred-page Machine Learning Book - Andriy Burkov
Amazon Machine Learning Developer Guild Version Latest
Building Chatbots with Python Using Natural Language Processing and Machine Learning - Sumit Raj
Deep Learning with Applications Using Python - Navin Kumar Manaswi
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Introduction to Deep Learning - Eugene Charniak
Machine Learning Applications Using Python - Cases studies form Healthcare, Retail, and Finance - Pu...
Machine Learning with spark and python - Michael Bowles
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Learn Keras for Deep Neural Networks - Jojo Moolayil
TensorFlow for Deep Learning - Bharath Ramsundar & Reza Bosagh Zadeh
Python Deep Learning Cookbook - Indra den Bakker
Deep Learning dummies first edition - John Paul Mueller & Luca Massaron
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
Python Machine Learning Cookbook - Practical solutions from preprocessing to Deep Learning - Chris A...
Python Machine Learning Second Edition - Sebastian Raschka & Vahid Mirjalili
Java Deep Learning Essentials - Yusuke Sugomori
An introduction to neural networks - Kevin Gurney & University of Sheffield
Fundamentals of Deep Learning - Nikhil Bubuma
Introduction to Deep Learning Business Application for Developers - Armando Vieira & Bernardete Ribe...
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Deep Learning Illustrated - A visual, Interactive Guide to Arficial Intelligence First Edition - Jon...
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Deep Learning for Natural Language Processing - Jason Brownlee
Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
Introduction to Machine Learning with Python - Andreas C.Muller & Sarah Guido
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
Grokking Deep Learning - MEAP v10 - Andrew W.Trask
Python Machine Learning Eqution Reference - Sebastian Raschka