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Core AI Algorithms Cheat Sheet: From Classical ML to Foundation Models & Vector Search
A production-tested reference guide distilling the 27 most essential algorithms used in modern AI engineering: covering classical supervised learning, gradient-boosted trees, clustering and vector search (HNSW), deep architectures and optimizers (AdamW), and LLM alignment (DPO, PPO).
Neural Networks Evolution History & Landmark AI Papers Cheat Sheet
A comprehensive reference guide charting the evolution of neural networks and deep learning (1850s to present): covering 8 historical eras, 18 seminal landmark papers, architectural transitions, core bottlenecks solved, and an analysis of the 4 foundational unsolved challenges in modern AI.