Téléchargez le livre : Deep Reinforcement Learning with Python

Deep Reinforcement Learning with Python

RLHF for Chatbots and Large Language Models de

Éditeur :

Apress


Paru le : 2024-07-13

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Description


Gain a theoretical understanding to the most popular libraries in deep reinforcement learning (deep RL).  This new edition focuses on the latest advances in deep RL using a learn-by-coding approach, allowing readers to assimilate and replicate the latest research in this field. 
New agent environments ranging from games, and robotics to finance are explained to help you try different ways to apply reinforcement learning. A chapter on multi-agent reinforcement learning covers how multiple agents compete, while another chapter focuses on the widely used deep RL algorithm, proximal policy optimization (PPO). You'll see how reinforcement learning with human feedback (RLHF) has been used by chatbots, built using Large Language Models, e.g. ChatGPT to improve conversational capabilities.
You'll also review the steps for using the code on multiple cloud systems and deploying models on platforms such as Hugging Face Hub. The code is in Jupyter Notebook, which canbe run on Google Colab, and other similar deep learning cloud platforms, allowing you to tailor the code to your own needs. 
Whether it’s for applications in gaming, robotics, or Generative AI, Deep Reinforcement Learning with Python will help keep you ahead of the curve.


What You'll Learn


Explore Python-based RL libraries, including StableBaselines3 and CleanRL  Work with diverse RL environments like Gymnasium, Pybullet, and Unity MLUnderstand instruction finetuning of Large Language Models using RLHF and PPOStudy training and optimization techniques using HuggingFace, Weights and Biases,      and Optuna 


Who This Book Is For
Software engineers and machine learning developers eager to sharpen their understanding of deep RL and acquire practical skills in implementing RL algorithms fromscratch. 
Pages
634 pages
Collection
n.c
Parution
2024-07-13
Marque
Apress
EAN papier
9798868802720
EAN PDF
9798868802737
Informations sur l'ebook
Nombre pages copiables
6
Nombre pages imprimables
63
Taille du fichier
26941 Ko
Prix
64,08 €
EAN EPUB
9798868802737
Informations sur l'ebook
Nombre pages copiables
6
Nombre pages imprimables
63
Taille du fichier
17132 Ko
Prix
64,08 €

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