📰 Machine Learning Mastery

In this article, you will learn how to get a small language model running locally on your own machine in under 15 minutes using Ollama....

In this article, you will learn how scikit-ollama bridges the scikit-learn interface with locally running Ollama models to perform zero-shot text classification

In this article, you will learn how to evaluate LLM applications using the three dominant open-source frameworks — RAGAS, DeepEval, and Promptfoo —

Agent systems change constantly in production.

In this article, you will learn how to choose the right memory strategy for an AI agent by working through a simple decision tree, one...

The default assumption in most LLM developer communities is that you start with raw API calls and graduate to a framework as your project grows.

Tools execute code.

You build an agent with five tools.

Compression on Arrival Tool outputs should be compressed after a call returns, not after the window fills.

In this article, you will learn five practical strategies for managing context windows in long-running AI agent applications, along with the key tradeoffs each

MCP provides a standard way for AI applications and external systems to communicate.

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In this article, you will learn how to distinguish agentic workflows from autonomous agents by focusing on who owns control flow &mdash; a human writing...

In this article, you will learn why a large context window is not the same thing as agent memory, and how techniques like retrieval, compression,...

The current era of Generative AI seems to primarily focus on chat interfaces and prompts, but the range of applications of large language models , or LLMs for s

Most AI agent tutorials start with an API.

Let's not waste any more time.

Traditional machine learning pipelines for predictive tasks like text classification usually rely on extracting structured, numerical features from raw text &md

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Transitioning from writing local experimental scripts to building scalable, production-grade AI systems requires a shift in how we write Python.

Text classification typically boils down to scenarios where a product review is "positive" or "negative", or a customer inquiry belongs to one category or anoth

Most browser AI tutorials cover text because it is a natural starting point, but the applications people actually want to build are rarely text-only.

According to Futurum Research's 2025 market overview of agentic AI platforms, <a href="https://zbrain.

You've probably shipped this bug before, where a user types " affordable laptop " into your search bar and gets zero results.