MLOps/LLMOps Course
Concepts of LLM Serving
LLMOps Part 14: An overview of the fundamentals of LLM serving, including API-based access, inference with vLLM, and practical decisions.
Archive
Latest
MLOps/LLMOps Course
LLM Inference and Optimization: Fundamentals, Bottlenecks, and Techniques
LLMOps Part 13: Exploring the mechanics of LLM inference, from prefill and decode phases to KV caching, batching, and optimization techniques that improve latency and throughput.
Claude
Claude Subagents vs. Agent Teams
...explained visually.
MLOps/LLMOps Course
LLM Fine-tuning: Techniques for Adapting Language Models
LLMOps Part 12: Understanding LLM fine-tuning, parameter-efficient methods like LoRA and QLoRA, and alignment techniques such as RLHF, DPO, and GRPO.
LLMs
Paged Attention in LLMs
...explained visually!
LLMs
Prompt Caching in LLMs!
A case study on how Claude achieves 92% cache hit-rate.
MLOps/LLMOps Course
Evaluation: Multi-turn Conversations, Tool Use, Tracing, and Red Teaming
LLMOps Part 11: Understanding evaluation of conversational LLM systems, tool evaluations, tracing with Langfuse, and automated red teaming.
MLOps/LLMOps Course
Evaluation: Model Benchmarks and LLM Application Assessment
LLMOps Part 10: Understanding model benchmarks, LLM application evaluation, and tooling.
