Benchmarking

A comprehensive guide for Go testing that covers table-driven tests, subtests, benchmarks, fuzzing, and test coverage. Follows TDD (Test-Driven Development) methodology with idiomatic Go practices and includes examples for mocking, HTTP handler testing, and CI/CD integration.

A comprehensive guide to profiling and optimizing Python code. Covers CPU and memory profiling tools (cProfile, memory_profiler, py-spy), optimization patterns like list comprehensions, caching with lru_cache, NumPy vectorization, and parallel processing with multiprocessing and asyncio.

This skill teaches comprehensive evaluation strategies for LLM applications, covering automated metrics (BLEU, ROUGE, BERTScore), human evaluation frameworks, LLM-as-Judge patterns using Claude, A/B testing with statistical analysis, and regression detection. It includes ready-to-use Python code examples and integrates with tools like LangSmith.

PyTDC (Therapeutics Data Commons) provides AI-ready datasets and benchmarks for drug discovery and development. It offers curated datasets spanning ADME, toxicity, drug-target interactions, and molecular generation with standardized evaluation metrics and meaningful data splits for therapeutic machine learning applications.