Data Science Tutorials

Learn what zero-shot classification is, how it works under the hood with NLI models, how it compares to few-shot and fine-tuning, and how to apply it with Hugging Face Transformers.

Connect the Claude Fable 5 API to a Python project and build a developer task assistant with structured JSON outputs, streaming, tool use, refusal handling, and a FastAPI endpoint.

A guide to Markov Chain Monte Carlo - covering how it works, why it’s used, the most common algorithms, and how to apply it in Python for Bayesian inference.

See how an end-to-end MLOps pipeline predicts World Cup 2026 results, from automated retraining and DVC to a 10,000-run Monte Carlo simulation of the bracket.

Gradient clipping is a one-line training fix that prevents exploding gradients from ruining deep neural network training. This guide covers how it works, the two main clipping methods, threshold selection, and implementation in PyTorch and TensorFlow.

Build a CrewAI agent swarm with Gemini 3.5 Flash, Olostep live web search, and hierarchical task delegation for a multi-agent research and writing workflow.

Build a Streamlit app that runs Claude Opus 4.8 with adaptive thinking, auto-scores each response with Haiku 4.5, and charts the cost-quality tradeoff.

Support Vector Regression is a margin-based regression method that ignores small errors intentionally, handles nonlinear relationships through kernels, and holds up on noisy real-world data where standard regression comes up short.

Learn how to use MiniMax M3 with MiniMax Code, a local and browser-based agentic coding engine for generating presentations, research reports, websites, games, and full complex projects in this in-depth hands-on review.

GitHub Copilot privacy settings changed in April 2026. Learn what data leaves your IDE, how to configure content exclusions, and how to fix common issues.

Learn how GitHub Copilot Enterprise uses Spaces and the Usage Metrics API to provide organizational context, governance, and adoption tracking across engineering teams.

GitHub Copilot has moved far beyond “AI autocomplete for code.” In 2026, the differences between GitHub Copilot plans come down to privacy boundaries, admin controls, auditability, and the governance your organization needs.