Companies Home Search Profile

Generative Deep Learning: Teaching Machines To Paint, Write, Compose, and Play

Generative Deep Learning: Teaching Machines To Paint, Write, Compose, and Play

Download pdf

Generative Deep Learning: Teaching Machines To Paint, Write, Compose, and Play

Generative Deep Learning: Teaching Machines To Paint, Write, Compose, and Play

Category

Artificial Intelligence

Deep Learning

Author

David Foster

Publication

OReilly Media

0 View

Generative modeling is one of the hottest topics in AI. It\'s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models such as variational autoencoders (VAEs), generative adversarial networks (GANs), Transformers, normalizing flows, energy based models, and diffusion models.

Author David Foster demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to some of the most cutting-edge algorithms in the field. Through tips and tricks, you\'ll understand how to make your models learn more efficiently and become more creative.

Discover how VAEs can change facial expressions in photos
Build practical GAN examples from scratch to generate images based on your own dataset
Create autoregressive generative models, such as LSTMs for text generation and PixelCNN models for image generation
Build music generation models, using Transformers and MuseGAN
Explore the inner workings of state-of-the-art architectures such as StyleGANGPT-3, and DDIM
Dive into the the detail of multimodal models such as DALL.E 2 and Imagen for text-to-image generation
Understand how generative world models can help agents accomplish tasks within a reinforcement learning setting
Understand how the future of generative modeling might evolve, including how businesses will need to adapt to take advantage of the new technologies

'

Download pdf

ISBN-10

1098134184

ISBN-13

978-1098134181

Publisher

OReilly Media

Price

69.99

File Type

PDF

Page No.

420

David Foster

David Foster is the co-founder of Applied Data Science, a data science consultancy delivering innova ...

About the Author

David Foster is a Founding Partner of ADSP, a consultancy delivering bespoke data science and AI solutions. He holds an MA in Mathematics from Trinity College, Cambridge and an MSc in Operational Research from the University of Warwick.

Through ADSP, David leads the delivery of high-profile data science and AI projects across the public and private sectors. He has won several international machine-learning competitions, including the Innocentive Predicting Product Purchase challenge and for delivering a process to enable a pharmaceutical company in the US to optimize site selection for clinical trials.

He is a member of the Machine Learning Institute Faculty and has given talks internationally on topics related to the application of cutting-edge data science and AI within industry and academia.

Similar Books

Artificial Intelligence and Machine Learning Methods in COVID-19 and Related Health Diseases (Studies in Computational Intelligence Book 1023)

Artificial Intelligence and Machine Learning Methods in COVID-19 and Related Health Diseases (Studies in Computational Intelligence Book 1023)

Victor Chang

Machine Learning

Applied Deep Learning: Tools, Techniques, and Implementation (Computational Intelligence Methods and Applications)

Applied Deep Learning: Tools, Techniques, and Implementation (Computational Intelligence Methods and Applications)

Paul Fergus

Artificial Intelligence

Intelligence - Theories and Applications

Intelligence - Theories and Applications

Rainer M. Holm-Hadulla

Artificial Intelligence

Regulation of Innovative Technologies: Blockchain, Artificial Intelligence and Quantum Computing

Regulation of Innovative Technologies: Blockchain, Artificial Intelligence and Quantum Computing

Rosario Girasa

Machine Learning and Non-volatile Memories

Machine Learning and Non-volatile Memories

Rino Micheloni

Machine Learning

Artificial Intelligence in Music, Sound, Art and Design: 11th International Conference, EvoMUSART 2022, Held as Part of EvoStar 2022, Madrid, Spain, April ... Notes in Computer Science Book 13221)

Artificial Intelligence in Music, Sound, Art and Design: 11th International Conference, EvoMUSART 2022, Held as Part of EvoStar 2022, Madrid, Spain, April ... Notes in Computer Science Book 13221)

Tiago Martins

Advances in Intelligent Data Analysis XX: 20th International Symposium on Intelligent Data Analysis, IDA 2022, Rennes, France, April 20–22, 2022, Proceedings (Lecture Notes in Computer Science, 13205)

Advances in Intelligent Data Analysis XX: 20th International Symposium on Intelligent Data Analysis, IDA 2022, Rennes, France, April 20–22, 2022, Proceedings (Lecture Notes in Computer Science, 13205)

Tassadit Bouadi

Artificial Intelligence

Artificial Intelligence/Machine Learning in Nuclear Medicine and Hybrid Imaging

Artificial Intelligence/Machine Learning in Nuclear Medicine and Hybrid Imaging

Patrick Veit-Haibach

Machine Learning

Security and Artificial Intelligence: A Crossdisciplinary Approach (Lecture Notes in Computer Science, 13049)

Security and Artificial Intelligence: A Crossdisciplinary Approach (Lecture Notes in Computer Science, 13049)

Lejla Batina

Artificial Intelligence

RoboCup 2021: Robot World Cup XXIV (Lecture Notes in Computer Science)

RoboCup 2021: Robot World Cup XXIV (Lecture Notes in Computer Science)

Oliver Obst

Artificial Intelligence

Language, Logic, and Computation: 13th International Tbilisi Symposium, TbiLLC 2019, Batumi, Georgia, September 16–20, 2019, Revised Selected Papers (Lecture Notes in Computer Science Book 13206)

Language, Logic, and Computation: 13th International Tbilisi Symposium, TbiLLC 2019, Batumi, Georgia, September 16–20, 2019, Revised Selected Papers (Lecture Notes in Computer Science Book 13206)

Aybüke Özgün

Artificial Intelligence

Advanced Artificial Intelligence and Robo-Justice

Advanced Artificial Intelligence and Robo-Justice

Georgios I. Zekos

Artificial Intelligence

Applied Deep Learning: Tools, Techniques, and Implementation (Computational Intelligence Methods and Applications)

Applied Deep Learning: Tools, Techniques, and Implementation (Computational Intelligence Methods and Applications)

Paul Fergus

Artificial Intelligence

Model Checking, Synthesis, and Learning: Essays Dedicated to Bengt Jonsson on The Occasion of His 60th Birthday (Lecture Notes in Computer Science Book 13030)

Model Checking, Synthesis, and Learning: Essays Dedicated to Bengt Jonsson on The Occasion of His 60th Birthday (Lecture Notes in Computer Science Book 13030)

Ernst-Rüdiger Olderog

Learning Strategies

Randomness and Elements of Decision Theory Applied to Signals

Randomness and Elements of Decision Theory Applied to Signals

Monica Borda

Decision Making

Deep Learning Techniques for IoT Security and Privacy (Studies in Computational Intelligence Book 997)

Deep Learning Techniques for IoT Security and Privacy (Studies in Computational Intelligence Book 997)

Nour Moustafa

Internet Of Things

Deep Learning for Unmanned Systems (Studies in Computational Intelligence Book 984)

Deep Learning for Unmanned Systems (Studies in Computational Intelligence Book 984)

Anis Koubaa

Computational Methods for Deep Learning: Theoretic, Practice and Applications (Texts in Computer Science)

Computational Methods for Deep Learning: Theoretic, Practice and Applications (Texts in Computer Science)

Wei Qi Yan

Machine Learning

Artificial Vision and Language Processing for Robotics: Create end-to-end systems that can power robots with artificial vision and deep learning techniques

Artificial Vision and Language Processing for Robotics: Create end-to-end systems that can power robots with artificial vision and deep learning techniques

Unai Garay Maestre

Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python

Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python

Yuxi (Hayden) Liu

Machine Learning

Deep Learning with PyTorch Lightning: Swiftly build high-performance Artificial Intelligence (AI) models using Python

Deep Learning with PyTorch Lightning: Swiftly build high-performance Artificial Intelligence (AI) models using Python

Kunal Sawarkar

Artificial Intelligence

Deep Natural Language Processing and Ai Applications for Industry 5.0 (Advances in Computational Intelligence and Robotics)

Deep Natural Language Processing and Ai Applications for Industry 5.0 (Advances in Computational Intelligence and Robotics)

Poonam Tanwar

Artificial Intelligence

Hands-On Python Deep Learning for the Web: Integrating neural network architectures to build smart web apps with Flask, Django, and TensorFlow

Hands-On Python Deep Learning for the Web: Integrating neural network architectures to build smart web apps with Flask, Django, and TensorFlow

Sayak Paul

Hands-On Deep Learning for IoT: Train neural network models to develop intelligent IoT applications

Hands-On Deep Learning for IoT: Train neural network models to develop intelligent IoT applications

Md. Rezaul Karim

Internet Of Things

Other Authors' Books

Other Publishing Books

Learning Domain-Driven Design: Aligning Software Architecture and Business Strategy

Learning Domain-Driven Design: Aligning Software Architecture and Business Strategy

Vlad Khononov

Software Architecture

CockroachDB: The Definitive Guide: Distributed Data at Scale

CockroachDB: The Definitive Guide: Distributed Data at Scale

Guy Harrison

SQL Server Advanced Troubleshooting and Performance Tuning: Best Practices and Techniques

SQL Server Advanced Troubleshooting and Performance Tuning: Best Practices and Techniques

Dmitri Korotkevitch

Advanced Analytics with PySpark: Patterns for Learning from Data at Scale Using Python and Spark

Advanced Analytics with PySpark: Patterns for Learning from Data at Scale Using Python and Spark

Akash Tandon

Snowflake: The Definitive Guide: Architecting, Designing, and Deploying on the Snowflake Data Cloud

Snowflake: The Definitive Guide: Architecting, Designing, and Deploying on the Snowflake Data Cloud

Joyce Avila

Cloud Computing

Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter

Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter

Wes McKinney

Python for Geospatial Data Analysis: Theory, Tools, and Practice for Location Intelligence

Python for Geospatial Data Analysis: Theory, Tools, and Practice for Location Intelligence

Bonny P McClain

Efficient Go: Data-Driven Performance Optimization

Efficient Go: Data-Driven Performance Optimization

Bartlomiej Plotka

Software Development

Foundations of Scalable Systems: Designing Distributed Architectures

Foundations of Scalable Systems: Designing Distributed Architectures

Ian Gorton

Software Development

Consul: Up and Running: Service Mesh for Any Runtime or Cloud

Consul: Up and Running: Service Mesh for Any Runtime or Cloud

Luke Kysow

Reliable Machine Learning: Applying SRE Principles to ML in Production

Reliable Machine Learning: Applying SRE Principles to ML in Production

Todd Underwood

Machine Learning

Operating OpenShift: An SRE Approach to Managing Infrastructure

Operating OpenShift: An SRE Approach to Managing Infrastructure

Manuel Dewald

Software Development

User Reviews

Log in first to post a comment

Rating

0

0

0

0

0

average 0

Total votes0