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Total Size:
9.3 MB
Info Hash:
4567070647DF961CB5C53ED62B1B7A71C7166268
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Added:
March 1, 2026, 6:57 p.m.
Stats:
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(Last updated: March 1, 2026, 7 p.m.)
| File | Size |
|---|---|
| Riti P. Introduction to Generative AI with Julia and Python. From Theory...2026.pdf | 9.3 MB |
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527.9 MB
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2025-03-09
| Uploaded by CorsaroNero | Size 527.9 MB | Health [ 0 /3 ] | Added 2025-03-09 |
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343.8 KB
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| Uploaded by hardcover | Size 343.8 KB | Health [ 19 /50 ] | Added 2024-09-12 |
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| Uploaded by GhostFreakXX | Size 817.6 MB | Health [ 17 /11 ] | Added 2024-08-29 |
NOTE
SOURCE: Riti P. Introduction to Generative AI with Julia and Python. From Theory...2026
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COVER
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MEDIAINFO
Textbook in PDF format
Elevate your coding capabilities and gain the skills necessary for maximized performance and career opportunities in the field of Artificial Intelligence. This book is a step-by-step guide designed to equip software engineers with solid foundation of Generative AI basics.
The book begins by introducing Generative AI using Google Colab to establish a solid foundation, before demonstrating how to leverage Python and Julia’s AI capabilities to construct Artificial Neural Networks. You’ll then explore advanced AI models, such as variational autoencoders, in order to generative images and text.
Author Pierluigi Riti not only navigates the complexities of this emerging topic but fills a crucial gap by guiding software engineers through theory before leading them to produce different types of models using only free resources.
This book explains what Generative Artificial Intelligence (GenAI) is, which is not a passing trend. It’s a technology that has come to stay. If you ask to someone for an example of GenAI, they might mention ChatGPT, Gemini, Claude, or any other Large Language Model (LLM), which are very good examples. However, the field is much bigger than that.
This book presents different uses of the GenAI, including generative adversarial networks, autoencoders, and variational-autoencoders. You will learn how these models learn and reproduce the data. This book also explains how to use Python and Julia to code for different flavors of the same architecture.
Every chapter is mixed with theory and practice, which will give you the basics to expand your knowledge and improve your skill. The book is not intended to explain the entire topic, but to be an introduction that you can use to improve and start your own journey in the field of the GenAI.
What You Will Learn:
Acquire a solid foundation of Generative AI basics.
Utilize the capabilities of Python and Julia to constructure Artificial Neural Networks
Explore advanced AI models including variational autoencoders, to generate images
Survey different architectures for AI and utilize free resources to produce different AI
Who This Book Is For:
Programmers new to Artificial Intelligence, but with a fundamental grasp of Python
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