Data Science Tutorials

Run Gemma 4 12B QAT locally with llama.cpp and see how Quantization-Aware Training improves 4-bit GGUF inference, reduces VRAM usage, boosts speed, and makes local AI more stable on consumer GPUs.

Learn how to clone your voice with Instant and Professional Voice Cloning in ElevenLabs, from recording clean audio to generating speech via the Python SDK.

Claude Code is not free by default. Learn about all alternative paths, with the exact setup commands and an honest account of what each one trades away from the original.

Learn how to fine-tune DiffusionGemma 26B-A4B for biomedical question answering on PubMedQA using Unsloth, LoRA, Hugging Face, and a RunPod H100 GPU.

Learn how to use Excel’s SUMIF() function to add values that meet a condition, with syntax explanations, practical examples, and common mistakes to avoid.

Learn how SARIMA extends ARIMA to handle seasonality, understand its seven parameters, and build a working model in Python from data collection through forecasting.

A hands-on guide to the silhouette score, covering the formula, interpretation ranges, a scikit-learn example, how to use it for choosing the right number of clusters, and how it compares to other clustering metrics.

Learn how to leverage Google's latest multimodal models to build high-performance, cost-effective image and video generation pipelines in Python.

Learn how to implement semantic search in MongoDB with Python. Generate vector embeddings, create a Vector Search index, and run $vectorSearch queries.

Learn how to use Grok in Microsoft Excel to analyze data, generate formulas, clean spreadsheets, create charts, and run financial scenarios using natural-language prompts.

Knowing why spurious relationships happen, from confounders to sampling bias, is what separates a real finding from a statistical coincidence.

A practical guide to hyperparameter tuning, covering how it works, the main search methods (grid, random, Bayesian), evaluation strategies, and how to run it in Python and R.