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Data Science Tutorials

Advance your data career with our data science tutorials. We walk you through challenging data science functions and models step-by-step.
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Data Science

Hessian Matrix: A Guide to Second-Order Derivatives in Optimization and Beyond

Understand the role of the Hessian matrix in multivariable calculus and optimization. Learn how it’s used to analyze curvature, locate critical points, and guide algorithms in machine learning.

Vidhi Chugh

June 16, 2025

Data Science

Orthogonal Matrix: An Explanation with Examples and Code

Learn about orthogonal matrices with practical examples and real-world applications in linear algebra and data science.
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Arunn Thevapalan

June 12, 2025

Data Science

Least Squares Method: How to Find the Best Fit Line

Use this method to make better predictions from real-world data. Learn how to minimize errors and find the most reliable trend line.
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Amberle McKee

June 12, 2025

Data Science

The T-Distribution: A Key Tool for Small Sample Inference

Understand how the t-distribution helps when sample sizes are small or population variance is unknown. Compare it to the normal and Z-distributions to learn when each is appropriate.
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Vidhi Chugh

June 11, 2025

Data Science

Law of Large Numbers: A Key to Understanding Uncertainty

Understand how the law of large numbers supports statistical reasoning. See how it ensures consistency in averages over time and powers predictions in fields like sports, finance, and science.
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Laiba Siddiqui

June 5, 2025

Data Science

The Sigmoid Function: A Key Component in Data Science

Explore the significance of the sigmoid function in neural networks and logistic regression, with practical insights for data science applications.
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Vikash Singh

May 28, 2025

Data Science

Triangle Inequality: From Geometry to Machine Learning

The triangle inequality is more than just a geometric principle - it's a cornerstone of distance measures in data science. Discover how this elegant mathematical concept powers algorithms across computational geometry, optimization, and machine learning.
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Vinod Chugani

May 27, 2025

Data Analysis

R-Squared Explained: How Well Does Your Regression Model Fit?

Learn what R-squared means in regression analysis, how to calculate it, and when to use it to evaluate model performance. Compare it to related metrics with examples in R and Python.
Elena Kosourova's photo

Elena Kosourova

May 14, 2025

Data Science

Time Series Decomposition: Understand Trends, Seasonality, and Noise

Learn how to break down time series data into meaningful components like trend, seasonality, and residuals using additive and multiplicative models. Learn about both classical and STL methods. Explore seasonal adjustments and practice forecasting with decomposition models.
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Josef Waples

Laiba Siddiqui's photo

Laiba Siddiqui

April 30, 2025

Data Science

Gaussian Elimination: A Method to Solve Systems of Equations

Learn the Gaussian elimination algorithm through step-by-step examples, code implementations, and practical applications in data science.
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Arunn Thevapalan

April 18, 2025

Data Science

Hamming Distance Explained: The Theory and Applications

Explore the fundamentals, applications, and comparisons of Hamming distance in various fields.
Vinod Chugani's photo

Vinod Chugani

April 16, 2025