Data Science Tutorials

A practical guide to Maclaurin series covering the core formula, common expansions, convergence rules, and real-world applications in numerical methods, physics, and machine learning.

Learn how to use the SQL RANK() function to assign rankings to rows, handle ties, and compare it with DENSE_RANK() and ROW_NUMBER().

Learn how to install and set up Hermes Agent, the open-source AI agent by Nous Research that remembers, learns, and grows smarter with every task.

This step-by-step guide teaches you to build a secure local AI agent with NanoClaw on Windows, connect it to WhatsApp, and control everything from the chat.

Learn how to run Meta's TRIBE V2 model on Google Colab, predict cortical activity from naturalistic stimuli, and visualize the results as interactive 3D brain heatmaps.

Learn how to create and use pivot tables in Google Sheets to summarize, analyze, and explore your data.

The F statistic is used to test whether a model explains variation in the data better than random chance. This guide explains what the F statistic means, how it is calculated, and how to interpret it.

Learn how to fine-tune Gemma 4 E4B-it on a human emotions dataset using LoRA, 4-bit quantization, and a single 3090 GPU.

Learn what an objective function is, how it works in optimization and machine learning, and how to define and interpret it with real examples.

Learn how to build a fully local, multimodal AI coding assistant powered by Gemma 4 via Ollama, featuring agentic tool use wrapped in Gradio UI.

Discover how Gemini Embedding 2 has revolutionized the way we can build search and RAG systems by introducing native multimodality. Text, video, images, and audio can now all live in the same embedding space.

Learn how to build a browser-based AI agent that searches the web, extracts live flight data, and returns clean recommendations using GLM-5-Turbo.