The RLHF Book
Nathan Lambert
This is a guide to reinforcement learning from human feedback (RLHF), alignment, and post-training for Large Language Models (LLMs). Author Nathan Lam...
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Nathan Lambert
This is a guide to reinforcement learning from human feedback (RLHF), alignment, and post-training for Large Language Models (LLMs). Author Nathan Lam...
Understand and apply the core algorithms of deep learning and artificial intelligence in this friendly illustrated guide including exercises and examples
Rishal Hurbans
Publisher
Manning
Published
2020
Duration
7 hr 25 min
ISBN
9781617296185
Genres
Description A visual guide to the fundamental algorithms that underpin artificial intelligence systems. It focuses on the intuition behind how intelligent systems learn, plan, and adapt, moving from classic search and optimization to modern deep learning and generative models.Key Topics: Classic search algorithms, reinforcement learning, genetic algorithms, neural networks for prediction, Large Language Model (LLM) pipelines, and image diffusion models. About the Technology: AI is a collection of computational algorithms designed to reason and learn. Foundational approaches in search and optimization provide the basis for more advanced systems like modern transformers and reinforcement learning agents. About the Book: The text utilizes illustrations, pseudocode, and creative coding exercises (such as building a maze solver or performing diamond data analysis) to explain algorithmic concepts without over-reliance on complex mathematics. About the Reader: For software developers and students who want to build an intuitive understanding of AI mechanics. About the Author: Rishal Hurbans is a software engineer and entrepreneur with a focus on designing and implementing intelligent systems across various industries.
