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Math

Models, measures, and first principles.

Notes on machine learning, probability, statistics, and the mathematics that makes the machinery intelligible.

Writing

5 articles

  1. 01Nov 2020 · Machine-Learning / StatisticsThe Bias-Variance Decomposition DemystifiedThis 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.
  2. 02Mar 2019 · Machine-LearningDeriving Machine Learning Cost Functions using Maximum Likelihood Estimation (MLE) - Part IICross-Entropy Loss - a commonly used cost function for binary classification problems derived using Maximum Likelihood Estimation (MLE)
  3. 03Mar 2019 · Machine-LearningDeriving Machine Learning Cost Functions using Maximum Likelihood Estimation (MLE) - Part IMean Squared Error (MSE) - a commonly used cost function for regression problems derived using Maximum Likelihood Estimation (MLE)
  4. 04Jan 2018 · Python / pandasdplyr-style Data Manipulation with Pipes in PythonTutorial on how to write chainable data manipulation code in Python.
  5. 05Jul 2016 · R / PlotlyExploratory Analysis of the Washington's Post Police Shooting dataset using R and PlotlyUsing R packages to perform exploratory data analysis on Police shooting dataset recorded in the United States.