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:

Artificial Intelligence - A Very Short Introduction - Margaret A.Boden
R Deep Learning Essentials - Dr. Joshua F.Wiley
Building Chatbots with Python Using Natural Language Processing and Machine Learning - Sumit Raj
Deep Learning in Python - LazyProgrammer
Python Artificial Intelligence Project for Beginners - Joshua Eckroth
Pro Deep Learning with TensorFlow - Santunu Pattanayak
Neural Networks - A visual introduction for beginners - Michael Taylor
Artificial Intelligence with an introduction to Machine Learning second edition - Richar E. Neapolit...
Coding Theory - Algorithms, Architectures and Application
Data Science and Big Data Analytics - EMC Education Services
Python Machine Learning Cookbook - Practical solutions from preprocessing to Deep Learning - Chris A...
Deep Learning with Python - Francois Cholletf
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Superintelligence - Paths, Danges, Strategies - Nick Bostrom
Deep Learning with PyTorch - Vishnu Subramanian
Artificial Intelligence by example - Denis Rothman
Deep Learning with Theano - Christopher Bourez
Pattern recognition and machine learning - Christopher M.Bishop
Introduction to Machine Learning with Python - Andreas C.Muller & Sarah Guido
Deep Learning from Scratch - Building with Python form First Principles - Seth Weidman
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Building Machine Learning Systems with Python - Willi Richert & Luis Pedro Coelho
Introduction to Deep Learning Business Application for Developers - Armando Vieira & Bernardete Ribe...
Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli
Deep Learning with Python - Francois Chollet
Java Deep Learning Essentials - Yusuke Sugomori
The hundred-page Machine Learning Book - Andriy Burkov
Machine Learning with spark and python - Michael Bowles
Python Machine Learning Third Edition - Sebastian Raschka & Vahid Mirjalili
Python Deep Learning Cookbook - Indra den Bakker
Deep Learning dummies second edition - John Paul Mueller & Luca Massaronf