Tag
machine learning
Machine learning spans model training, feature engineering, inference, and evaluation, and now reaches explainability, ranking systems, trading bots, and agentic AI. This tag tracks practical use cases and the methods behind them, from manufacturing XAI to ad ranking and production deployment.
9 articles
awesome-ai-summerschool turns AI events into a shortlist
I break down a GitHub list that turns AI summer schools into a usable shortlist, plus a copy-ready template to reuse.
5 blockchain AI market signals for buyers
5 market signals show blockchain AI could grow from $740M in 2025 to $6.44B by 2034.
Selective LLM Regularization for Recommenders
A paper on using selective LLM-guided regularization to improve recommendation models without overhauling the recommender stack.
LLMs plus knowledge graphs for ML explainability
A manufacturing XAI method uses a knowledge graph plus an LLM to turn ML results into clearer, more user-friendly explanations.
Meta’s ad serving tweak lifts Instagram results
Meta says its Adaptive Ranking Model improved Instagram ads, lifting conversions 3% and click-through rates 5% with real-time signals.
How to Build an AI Crypto Trading Bot
A practical 2026 guide to AI crypto bots: data, models, risk controls, deployment, and compliance for production use.
2026 AI roadmap repo maps ML to agentic AI
A tiny GitHub repo with 1 star lays out a 2026 path from ML basics to agentic AI, with tools, projects, and roles.
A Practical GitHub Guide to Learning ML in 2026
Louis Bouchard’s GitHub guide bundles free ML and AI learning resources for beginners, with courses, videos, math refreshers, and job advice.
Claude Usage Diversifies, Learning Curves Emerge
Anthropic's February 2026 report reveals a shift in Claude's usage patterns, highlighting increased personal queries and evolving user proficiency.