Data Analytics

  #  Corruption with Delegation   We are entering a new AI era, in which interaction turns into work delegation. Users not only just chat with an AI that answers their questions: they increasingly delegate long-horizon tasks — from editing source code to formatting professional text or even managing accounting books. Therefore, they trust AI…

  #  Introduction   Writing to files is an essential Python skill. It lets you save data permanently instead of losing it when your program stops. You can use file saving to store results, logs, reports, user input, settings, and structured data. In this guide, you will learn how to create text files, write multiple…

  #  Introduction   For a long time, running transformer models meant maintaining a Python server, paying for GPU time, and routing every inference request through an API. The user typed something, it left their machine, touched your infrastructure, and came back as a prediction. That architecture made sense when the models were too large…

  #  Introduction   In a recent article on Machine Learning Mastery, we built a tool-calling agent that reached outward, that is pulling weather, news, currency rates, and time from public APIs. That article covered the synthesis half of the pattern nicely, but it left the more interesting half on the table: an agent that…

  #  Introduction to Claude Cowork   Most people who use Claude like a smarter search engine. Type something in, read the response, copy it somewhere useful, then come back and do it again. That loop works fine for quick questions. It does not work for the kind of deep, file-heavy, multi-step knowledge work that…

  #  Introduction   Time series feature engineering doesn't follow the same rules as tabular data. Observations aren't independent, row order isn't incidental, and the most useful features are rarely individual readings. You'll have to identify patterns across time like rates of change, lag comparisons, deviations from a rolling baseline, and more. Building lags, sliding…

  #  Introduction   JSON is great for APIs, storage, and application logic. But inside large language model (LLM) pipelines, it often carries a lot of token overhead that does not add much value to the model: braces, quotes, commas, and repeated field names on every row. TOON, short for Token-Oriented Object Notation, is a…

  #  Introduction   Everyone focuses on writing SQL that "works," but very few test whether it keeps working tomorrow. A single new row, a changed assumption, or a refactor can break a query silently. This article walks through a complete workflow, showing how to treat SQL like software: versioned, tested, and automated. We'll use…

Image by Editor   #  The Self-Hosted LLM Problem(s)   "Run your own large language model (LLM)" is the "just start your own business" of 2026. Sounds like a dream: no API costs, no data leaving your servers, full control over the model. Then you actually do it, and reality starts showing up uninvited. The…

Image by Author   #  Introduction   OpenClaw is quickly becoming one of the most talked-about open-source agent systems right now. But beyond the hype, the real question is simple: what are people actually using it for? At its core, OpenClaw helps turn AI from something you chat with into something that can actually do…