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Generative Deep Learning with Python
Generative Deep Learning with Python

Generative Deep Learning with Python: Unleashing the Creative Power of AI by Mastering AI and Python

By Cuantum Technologies LLC
€25.99
Book Jun 2024 276 pages 1st Edition
eBook
€25.99
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eBook
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Generative Deep Learning with Python

Code Blocks Resource

 

To further facilitate your learning experience, we have made all the code blocks used in this book easily accessible online. By following the link provided below, you will be able to access a comprehensive database of all the code snippets used in this book. This will allow you to not only copy and paste the code, but also review and analyze it at your leisure. We hope that this additional resource will enhance your understanding of the book's concepts and provide you with a seamless learning experience.

 

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www.cuantum.tech/books/generative-deep-learning-with-python/code/

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Key benefits

  • Comprehensive coverage of deep learning and generative models.
  • In-depth exploration of GANs, VAEs, & autoregressive models & advanced topics in generative AI.
  • Practical coding exercises & interactive assignments to build your own generative models.

Description

Generative Deep Learning with Python opens the door to the fascinating world of AI where machines create. This course begins with an introduction to deep learning, establishing the essential concepts and techniques. You will then delve into generative models, exploring their theoretical foundations and practical applications. As you progress, you will gain a deep understanding of Generative Adversarial Networks (GANs), learning how they function and how to implement them for tasks like face generation. The course's hands-on projects, such as creating GANs for face generation and using Variational Autoencoders (VAEs) for handwritten digit generation, provide practical experience that reinforces your learning. You'll also explore autoregressive models for text generation, allowing you to see the versatility of generative models across different types of data. Advanced topics will prepare you for cutting-edge developments in the field. Throughout your journey, you will gain insights into the future landscape of generative deep learning, equipping you with the skills to innovate and lead in this rapidly evolving field. By the end of the course, you will have a solid foundation in generative deep learning and be ready to apply these techniques to real-world challenges, driving advancements in AI and machine learning.

What you will learn

Develop a detailed understanding of deep learning fundamentals Implement and train Generative Adversarial Networks (GANs) Create & utilize Variational Autoencoders for data generation Apply autoregressive models for text generation Explore advanced topics & stay ahead in the field of generative AI Analyze and optimize the performance of generative models

Product Details

Country selected

Publication date : Jun 12, 2024
Length 276 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781836207139
Category :
Concepts :

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
Buy Now

Product Details


Publication date : Jun 12, 2024
Length 276 pages
Edition : 1st Edition
Language : English
ISBN-13 : 9781836207139
Category :
Concepts :

Table of Contents

17 Chapters
1. Code Blocks Resource Chevron down icon Chevron up icon
2. Premium Customer Support Chevron down icon Chevron up icon
3. Who we are Chevron down icon Chevron up icon
4. Introduction Chevron down icon Chevron up icon
5. Chapter 1: Introduction to Deep Learning Chevron down icon Chevron up icon
6. Chapter 2: Understanding Generative Models Chevron down icon Chevron up icon
7. Chapter 3: Deep Dive into Generative Adversarial Networks (GANs) Chevron down icon Chevron up icon
8. Chapter 4: Project: Face Generation with GANs Chevron down icon Chevron up icon
9. Chapter 5: Exploring Variational Autoencoders (VAEs) Chevron down icon Chevron up icon
10. Chapter 6: Project: Handwritten Digit Generation with VAEs Chevron down icon Chevron up icon
11. Chapter 7: Understanding Autoregressive Models Chevron down icon Chevron up icon
12. Chapter 8: Project: Text Generation with Autoregressive Models Chevron down icon Chevron up icon
13. Chapter 9: Advanced Topics in Generative Deep Learning Chevron down icon Chevron up icon
14. Chapter 10: Navigating the Future Landscape of Generative Deep Learning Chevron down icon Chevron up icon
15. Conclusion Chevron down icon Chevron up icon
16. Where to continue? Chevron down icon Chevron up icon
17. Know more about us Chevron down icon Chevron up icon

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