Choosing a local LLM comes down to one number: how much memory you have. The best open models for 8GB, 16GB, 24GB and 48GB+ machines, plus quantisation explained and what local still does badly.
No forecasting model wins outright - they differ in what they assume, how much data they need and whether anyone can explain the output. Four families compared, with the validation mistake that invalidates most forecasting work.
Most ML projects fail eight months after deployment, not during training. What MLOps actually involves - the five capabilities, four maturity levels, why drift is the failure nobody sees, and where to start.
No MLOps tool does everything well. The market is five layers wearing one label - tracking, versioning, orchestration, serving, monitoring - with a clear default in each and three stacks that actually work.
You are not choosing one data pipeline tool - you are assembling two or three. The 12 that matter, organised by the stage they handle, plus three stacks that actually work and the mistakes that create pipeline debt.
A practical ranking of the 9 best AI video generators in 2026 - Veo, Runway, Kling, Synthesia, HeyGen and more - plus what the Sora shutdown means and the real cost per finished minute.
