Optuna Tutorial: Automate Hyperparameter Tuning for ML Models in Python How Optuna's define-by-run API, TPE sampler, and pruners automate hyperparameter tuning
Several recent posts explore advancements and applications in AI agents, particularly for coding and reasoning tasks. Topics include building autonomous coding agents that can open GitHub pull requests, using patterns like Continual Harness for self-improving agents, and integrating tools like Cursor into agent workflows. The limitations of LLM reasoning in causal inference and new approaches to browser fingerprinting for web scraping are also discussed, alongside efforts to automate hyperparameter tuning for machine learning models. AI
IMPACT Explores practical applications and limitations of AI agents in coding, reasoning, and web scraping, offering insights for developers.