3 Statsmodels Tricks for Time Series Analysis & Forecasting
A fitted statsmodels model computes a more than just the array of numbers most code pulls out of it.
38 stories
A fitted statsmodels model computes a more than just the array of numbers most code pulls out of it.
This is the Python material that does not get left behind. Almost none of it is replaced by a framework later. Learn it, and keep this cheat sheet close by as a handy reference.
The forward deployed engineer: is this the hot new AI career, or has the hype cycle rebranded?
Reduce costs, improve response quality, and build leaner AI applications with these prompt engineering strategies.
Describe your data needs in plain language and turn websites into a continuous source of fresh data.
Docling takes documents in whatever inconsistent format they arrive in, and converts them into one unified, structured representation that both people and AI systems can work with reliably, rather than everyone downstream having to guess at what a wall of extracted text actually meant.
Learn how to use Marimo for interactive data analysis with Python, Pandas, and Altair, and turn a reactive notebook into a simple shareable dashboard.
Get work done, and have seconds added back to your life since you won't be writing second, third or — *gasp!* — fourth line follow-ups to your impeccable typed line numero uno.
OpenAI’s agents reached a proposed solution in 88 hours. But the human research that came before, and the controversy that followed, raise a harder question: what actually counts as an AI discovery?
Ollama pulls model weights, keeps an HTTP server on port 11434, and hands any client an OpenAI-shaped endpoint pointed at your own machine. Learn how to manage, configure, and optimize using Ollama right here.
Learn how to use Julius AI to analyze Excel data, verify key findings, and turn them into an editable PowerPoint presentation.
This is a summary of, and insights into, what I found digging into the recently-released Superwhisper S1 family of voice-to-text models.
Learn LLM fundamentals, AI engineering, RAG, MLOps, fine-tuning, and deployment with five practical courses designed to help you become a stronger AI and machine learning engineer.
Here's how each got to where it is, a real use case and working code for both, and a side-by-side on the numbers that actually matter.
When Numba code disappoints, it's nearly never the compiler, and usually ends up being the boundary around the compiled code: not crossing it, not making it wide enough, or crossing it during every run.
We finish off our short series on SLM optimization with the third entry, focused on batching by length instead of looping item by item.
Leveling up rarely means new syntax. It means learning what the language already promised you.
A visual guide to MCP that explains how it works, how to use it with Claude Code, Tavily, GitHub, and Playwright, and what is new through simple diagrams that make the whole concept easy for anyone to understand.
Showing 36 of 38 stories
Load more storiesGet the top AI news and tools straight to your inbox every week.
Weekly · AI news
Join 15,000+ AI enthusiasts