Linear Algebra for AI Developers
Organize linear algebra resources for AI developers, focusing on ML and DL applications. Prioritize practical learning paths and avoid beginner pitfalls.
Ml
Where RL Fits: Training vs. Inference in the LLM Pipeline
Explains that RL in LLMs is a training/alignment stage, not inference, with pipeline context.
Reinforcement Learning (ELI-Teen Explainer)
Teen-friendly explainer of reinforcement learning agents, rewards, exploration, delayed rewards, and applications.
Model Type Classification by Modality (Multimodal, Vision, Image Generation)
Classifies multimodal, vision, and image-generation models by their input/output modalities.
TurboQuant
Explains TurboQuant, a rotation-based vector quantization method for KV-cache compression and vector search.
Anti-Narration in Harness Engineering
Harness pattern that forces verification before accepting fluent AI outputs as correct.
Model Drift
Overview of model drift, detection, mitigation, and LLM-specific issues like knowledge staleness and provider drift.
Attention in Machine Learning
Explanation of the attention mechanism in ML, covering Query/Key/Value, self-attention, multi-head, causal, cross-attention, and efficiency variants like FlashAttention and GQA.
Fine-Tuning Techniques for LLMs
Comprehensive guide to LLM fine-tuning methods including full, parameter-efficient, and preference-based approaches with modern recipes and tools like LoRA and DPO
Unsloth Studio — Fine-tuning Dataset Formats
Overview of dataset formats supported by Unsloth Studio for fine-tuning, including JSONL, Alpaca, ShareGPT, ChatML, and Reasoning formats with rules and best practices and dataset size guidelines
Mixture of Experts (MoE)
Overview of MoE architecture, routing, key components, variants, and trade-offs in machine learning models
Chain of Thought (CoT)
Prompting technique where an AI model is guided — or learns — to reason through a problem step by step before arriving at the final answer, rather than jumping straight to the conclusion.
Visual Chain-of-Thought Reasoning
Extension of chain-of-thought prompting to multimodal settings where models reason step-by-step over both visual and textual information.
Agent Harness Engineering
Overview of agent harness engineering — the scaffolding, infrastructure, and tooling surrounding an AI agent, covering execution environments, tool orchestration, memory management, control flow, tracing, safety, and state persistence
Diffusion Models in AI
Overview of diffusion models, how they reverse a gradual noising process to generate data, key variants like DDPM, DDIM, and Latent Diffusion Models, and how text-to-image conditioning works