Data Science Tutorials

Discover how Polars read_csv() helps you load CSV data efficiently in Python, including handling large datasets, defining schemas, and optimizing performance.

Build a Python visual repair agent with DeepSeek V4.1 Flash, the Responses API, Playwright screenshots, apply_patch, pytest, context caching, and cost tracking.

Build and run a cloud agent with the OpenAI Agents API that can analyze files, execute code, verify results, and return finished artifacts from a single request.

Learn how to use the VBA InStr function to find text inside strings, including syntax, examples, case sensitivity, and common mistakes.

Learn what statistical arbitrage is, how quantitative traders identify temporary pricing relationships, and how strategies such as pairs trading and mean reversion work in practice.

Run the optimized Motif-3 Quant on an NVIDIA H200 using the ds4 runtime, serve it through an OpenAI-compatible API, and integrate it with a Pi coding agent.

Learn how to set up the Kimi Browser Extension using both Kimi Work and Kimi Code CLI, and run a product search that extracts structured results from a website.

Flow matching trains generative models to turn noise into data by learning a vector field that moves samples along a chosen probability path, the same idea driving continuous normalizing flows and modern diffusion models.

Deep reinforcement learning combines the trial-and-error loop of reinforcement learning with neural networks that generalize across huge state spaces.

Learn what recursive self-improvement means in AI, how AI systems can help develop better AI, how close today's models are to RSI, and why the concept matters for AI capabilities and safety.

Learn how vision-language-action (VLA) models work, how they differ from VLMs, and how to choose between OpenVLA, pi0, and SmolVLA in 2026.

Learn how to clear formatting in Excel using the Clear Formats tool, shortcuts, and other methods while keeping your data intact.