Data Science Tutorials

Learn the differences between Git Fetch and Git Pull in this comparison guide.

Learn the mathematical foundations, discover multiple types and their applications, and explore how standard error enhances statistical inference and decision-making.

Feed-Forward Neural Networks (FFNNs) are the foundation of deep learning, used in image recognition, Transformers, and recommender systems. This complete FFNN tutorial explains their architecture, differences from MLPs, activations, backpropagation, real-world examples, and PyTorch implementation.

Learn to set up and use LangExtract for extracting structured data and relationships from unstructured text, comparing its approach to traditional NLP libraries.

Learn how to install Azure CLI on any platform, authenticate securely, and manage Azure resources efficiently. Discover commands, tips, and automation techniques to boost your productivity.

Secure MongoDB from NoSQL injection by validating input, securing queries, and using defense-in-depth. Learn attack patterns and prevention in this guide.

Learn what GitHub Models are and how they enhance productivity by integrating AI capabilities into development workflows.

Learn how to turn any PDF into an interactive research assistant using DeepSeek V3.1 and a Streamlit app.

Learn how to group data by multiple columns in SQL to perform advanced aggregations. Explore use cases, performance tips, and practical examples.

Learn the essential statistical concept that gives proper weight to different data points. This comprehensive guide covers everything from basic calculations to real-world applications in finance, academics, and data analysis, with hands-on examples in Excel and Python.

Master the MongoDB Query API with this comprehensive guide to CRUD operations, advanced filters, data aggregation, and performance-boosting indexing.

Learn how to build reliable AI agents with Pydantic AI in Python. Validate outputs, use tools, and stream insights with practical code examples.