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Hello! I’m Matheus C. Pestana, a professor of data science and a practicing data scientist and political scientist.

This website is dedicated to sharing my knowledge and passion for data science with a broader audience. Here, you’ll find a variety of resources including tutorials, essays, tips, and other content designed to help you deepen your understanding of data science and stay updated with the latest trends and techniques in the field.

Whether you’re a student, a professional, or just someone with a keen interest in data science, I hope you’ll find the content here informative and inspiring. Feel free to explore, learn, and engage with the materials provided. Let’s embark on this data-driven journey together!

From Pandas to Polars

Migrating from Pandas to Polars: A Concise Tutorial If you’re a data scientist or analyst familiar with Pandas and are considering switching to Polars for its performance benefits, this guide will help you make the transition smoothly. I’ll cover the key differences and provide examples to get you up and running with Polars. Why Polars? Polars is a DataFrame library designed for high-performance data manipulation and analysis. It leverages Rust’s speed and efficiency, offering significant performance improvements over Pandas, especially with large datasets....

KANs - New Era of Data Science

In this blog post, I will try to explain the fascinating (but not new) world of Kolmogorov-Arnold Networks (KANs). I will explore how they differ from the more commonly known Multi-Layer Perceptrons (MLPs), discuss their strengths and weaknesses, and provide examples to illustrate their applications. What are Kolmogorov-Arnold Networks? Kolmogorov-Arnold Networks are named after the Kolmogorov-Arnold representation theorem. This theorem states that any continuous function of several variables can be represented as a superposition of continuous functions of one variable and addition....