Python Tutorial

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.

Enhance your visualizations with Matplotlib colormaps. Learn to pick the right colormap, adjust color classes, and troubleshoot common visualization issues.

Learn about Snowflake Cortex AI and how it can be used for LLMs and machine learning.

Explore how linear search works and why it’s ideal for small, unsorted datasets. Discover simple Python implementations, including iterative and recursive methods, and learn when to choose linear search over other algorithms.

Create standout bar charts using Matplotlib, Seaborn, Plotly, Plotnine, and Pandas. Explore bar chart types, from simple vertical and horizontal bars to more complex grouped and stacked layouts.

Explore everything you need to know about how to implement the bag of words model in Python.

Discover the essentials of depth-first search for navigating graphs and trees. Implement DFS in Python using recursion and iteration, and see how DFS compares to breadth-first search and Dijkstra’s algorithm.