Deep Reinforcement Learning Hands-On — Practical easy-to-follow guide to RL from Q-learning and DQNs to PPO and RLHF: http://
amzn.to/3MV9o60 [3rd Ed.] ——
#AI #MachineLearning #ML #DataScience ——
𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼:
Learn with concise explanations, modern libraries, and
MACHINE LEARNING
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Practical Guide to Deep Reinforcement Learning and RLHF
By
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Deep Learning Applications in Physics Research
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Deep Learning for Physics Research: http://
amzn.to/3ubQWQG
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#DataScientist #AI #MachineLearning #ML #NeuralNetworks #ComputerVision #ObjectDetection #DataScience -
New Book Release on Transfer Learning for Machine Learning Systems
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TRANSFER LEARNING book [390 pages]: http://
amzn.to/3R4G0zm Amazon Summary:
"Transfer learning deals with how systems can quickly adapt themselves to new situations, tasks and environments. It gives machine learning systems the ability to leverage auxiliary data and models to -
A Comprehensive Learning Path for Aspiring AI Developers
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AI Mastery >> The Complete Machine Learning Engineer Cookbook for Everyone — Become an AI Developer with Python: http://
amzn.to/3XZTzQS Complete 5-part Learning Path:
1 – Build Your Foundation
2 – Assemble Your ML Toolkit
3 – Discover Deep Learning & Generative AI
4 – Master -
Python Feature Engineering Cookbook for Machine Learning Models
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3rd Edition! "Python Feature Engineering Cookbook", complete guidebook with recipes for crafting powerful features for #MachineLearning models: http://
amzn.to/4rDWUT9 by @Soledad_Galli —————
#AI #ML #DataLiteracy #DataScience #DataScientist -
50 ML Projects for Understanding LLMs and Transformer Mechanisms
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50 ML projects to understand LLMs — Investigate transformer mechanisms through data analysis, visualization, and experimentation: http://
amzn.to/4aPfP7q
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#AI #GenAI #MachineLearning #DataScientist #DataScience -
New Book Release: Machine Learning Foundations Volume 1
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New Release! "Machine Learning Foundations, Volume 1: Supervised Learning" – available at http://
amzn.to/4syhPal 𝗕𝗘𝗡𝗘𝗙𝗜𝗧𝗦: Master the key concepts of supervised machine learning, including model capacity, the bias-variance tradeoff, generalization, and optimization -
Practical Guide to Building LLM and RAG Apps with LangChain
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"Generative AI and RAG for Beginners: A Practical Step-by-Step Guide to Building LLM and RAG Applications with LangChain and Python" Get your copy at http://
amzn.to/3MZZ9R5 Independently published: December 2025
Print length: 255 pages -
AI Agents and World Models: Research on Predictive Planning
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Can AI agents see into the future before acting? A team from UIUC, THU, JHU, and Columbia tested exactly that. They gave agents generative world models—external simulators that could predict outcomes before taking action. The result? Most agents refuse to simulate (under 1%
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Ways to Train an LLM
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Ways to Train an #LLM
by @goyalshaliniuk #GenAI #ArtificialIntelligence #MachineLearning #ML