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The Bias-Variance Decomposition Demystified
This post provides an intuitive explanation of the bias-variance decomposition. The bias-variance decomposition shows the generalisation error of a learning algorithm as the sum of three terms - bias, variance, and the irreducible error.
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Deriving Machine Learning Cost Functions using Maximum Likelihood Estimation (MLE) - Part II
Cross-Entropy Loss - a commonly used cost function for binary classification problems derived using Maximum Likelihood Estimation (MLE)
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Deriving Machine Learning Cost Functions using Maximum Likelihood Estimation (MLE) - Part I
Mean Squared Error (MSE) - a commonly used cost function for regression problems derived using Maximum Likelihood Estimation (MLE)
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dplyr-style Data Manipulation with Pipes in Python
Tutorial on how to write chainable data manipulation code in Python.
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Exploratory Analysis of the Washington's Post Police Shooting dataset using R and Plotly
Using R packages to perform exploratory data analysis on Police shooting dataset recorded in the United States.