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Reinforcement Learning Essentials: MDPs & Optimal Control
A comprehensive guide to understanding Markov Decision Processes, Policy Iteration, Value Iteration, and achieving optimal behavior in RL.
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Beyond Supervised Learning: Unlocking AI's Potential with Reinforcement Learning
Understand the fundamental shift RL offers, its core components, real-world applications, and the advanced challenges driving the future of intelligent systems.
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Implementing GPT-Style Attention: A Step-by-Step Guide with PyTorch
Learn how to build and optimize attention mechanisms for transformer models, from basic self-attention to the multi-head attention architecture used in state-of-the-art language models
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The Ultimate Guide to Preparing Text Data for Language Modeling with PyTorch
Master tokenization, Byte Pair Encoding, Sampling windows, and Embeddings
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PyTorch in Practice: Essential Building Blocks for Modern Deep Learning