Data Science Tutorials

Learn how to set up Claude Code Remote Control and connect your phone or browser to a live local session. We cover session modes, mobile access, and key limitations.

Learn how to use git stash to save, inspect, restore, and manage changes. Understand selective stashing, conflict fixes, and best practices for clean workflows.

Build reliable AI apps faster by turning ad-hoc prompt checks into structured LLM evaluations with Promptfoo, from local test suites to automated CI.

Use four essential commands (add, pull, push, split) to keep shared libraries in sync across teams.

Learn how to check and update your Git version across Windows, macOS, and Linux with easy commands to access the latest features and bug fixes.

A practical guide to `docker init` - what it generates, how to use it with a real Python project, and when it's the right tool for the job.

Master Terraform import of existing cloud resources with CLI commands and import blocks to bring legacy infrastructure under Infrastructure as Code management.

Solve beginner‑friendly Python exercises, starting with simple variables and building up to functions, data structures, and guided projects.

Learn about the definition, formula, key properties, homogeneous coordinates, and applications of affine transformations in graphics, computer vision, robotics, and data preprocessing.

Explore how polynomial regression helps model nonlinear relationships and improve prediction accuracy in real-world datasets.

Learn how Karpathy's AutoResearch runs 100+ ML experiments overnight on a single GPU. Covers the three-file architecture, ratchet loop, results, and limitations.

Learn about LIFO principles, how to implement stacks in Python using lists, deque, and LifoDeque, and apply them for undo/redo systems or graph traversal.