Data Science Tutorials

A walkthrough of Autoencoders, their variations, and potential applications in the real world.

This guide walks you through the basics of the ChatGPT API, demonstrating its potential in natural language processing and AI-driven communication.

Discover the power of prompt engineering in LangChain, an essential technique for eliciting precise and relevant responses from AI models.

Learn how to set up and configure MySQL database inside Docker containers. The tutorial includes concepts such as connecting to MySQL servers, running MySQL clients to connect to containers, and so on.

Learn how to easily select multiple columns from a database table in SQL, or select all columns from a table in one simple query.

The Python SDK provides convenient access to Anthropic's powerful conversational AI assistant Claude 2, enabling developers to easily integrate its advanced natural language capabilities into a wide range of applications.

Learn what R Markdown is, what it's used for, how to install it, what capacities it provides for working with code, text, and plots, what syntax it uses, what output formats it supports, and how to render and publish R Markdown documents.

A comprehensive overview of the Assistants API with our article, offering an in-depth look at its features, industry uses, setup guidance, and best practices to maximize its potential in various business applications.

OpenAI’s TTS API is an endpoint that enables users to interact with their TTS AI model that converts text to natural-sounding spoken language.

A comprehensive visual guide into skewness/kurtosis and how they effect distributions and ultimately, your data science project.

A tutorial on integrating Google SERP, DuckDuckGo, Wikipedia, and YouTube into GPT models using Python and LangChain tools.

See how a confusion matrix categorizes model predictions into True Positives, False Positives, True Negatives, and False Negatives. Keep reading to understand its structure, calculation steps, and uses for handling imbalanced data and error analysis.