Python Tutorial

Understand the basics of Reinforcement Learning (RL) and explore the Gymnasium software package to build and test RL algorithms using Python.

This beginner-friendly tutorial will guide you through the fundamentals of Metaflow. Learn how the framework simplifies building and scaling data science workflows.

Learn how to use pytest-mock, from setup and fundamentals to advanced techniques for practical testing.

Understand the core concepts of Self Organizing Maps and learn how to implement them in Python using MiniSom.

Learn to build effective command-line interfaces in Python using the argparse module. This guide walks you through basic and advanced features, with practical examples and tips to improve your programming skills.

Master Python's f-strings, the most elegant way to handle string formatting in your code. This guide covers everything from basic syntax to advanced techniques. Learn how to write cleaner, more maintainable code with real-world examples.

Learn how to validate your data with Great Expectations in Python with this end-to-end tutorial!

.loc selects data using row and column names (labels), while .iloc uses numerical indices (positions). Learn how to use both with examples.

Learn the first principles of Proximal Policy Optimization, including its implementation in PyTorch with Gymnasium!

Learn how to detect multicollinearity in regression models using the variance inflation factor (VIF), a key diagnostic tool. This tutorial explains how VIF is calculated, how to interpret its values, and techniques for addressing high VIF to improve the reliability of your regression modeling.

Learn how to fix Pandas' SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame.

Learn how to manage dependencies and virtual environments for complex projects using Python Poetry.