Data Science Tutorials

Learn how to run Alpaca-LoRA on your device with this comprehensive guide. Discover how this open-source model leverages LoRA technology to offer a powerful yet efficient AI chatbot solution.

This tutorial covers the basics of data pipelines and terminology for aspiring data professionals, including pipeline uses, common technology, and tips for pipeline building.

Learn how to use ggplot2 in R to create compelling visualizations of climate change data. This step-by-step tutorial teaches you to find, analyze, and visualize historical weather data.

Discover how Textacy, a Python library, simplifies text data preprocessing for machine learning. Learn about its unique features like character normalization and data masking, and see how it compares to other libraries like NLTK and spaCy.

This tutorial provides an introduction to causal AI using the DoWhy library in Python. It discusses fundamental principles and offers code examples.

Uncover the intricacies of non-linear models in comparison to linear models. Learn about their applications, limitations, and how to fit them using real-world data sets.

Learn what BigQuery is, how it works, its differences from traditional data warehouses, and how to use the BigQuery console to query public datasets provided by Google.

One table to rule them all: simplify, scale, and supercharge your NoSQL database!

With Chroma DB, you can easily manage text documents, convert text to embeddings, and do similarity searches.

Learn how OpenAI's new Function Calling capability enables GPT models to generate structured JSON output, resolving common dev issues caused by irregular outputs.

Build TCP clients and servers from scratch, handle multiple connections with threading, and learn when to reach for asyncio instead.

Uncover actionable insights hidden in complex signal data by filtering noise, choosing appropriate visualizations, finding patterns in the time- and frequency-domain, and more using signal processing.