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Tommy Khoo, Ph.D.

Data Science - Machine Learning and Statistics - Software Development

Education

PhD in Mathematics - Dartmouth College

MSc in Mathematics and the Foundations of Computer Science - Oxford University

BSc in Mathematics and Economics - Singapore Institute of Management, University of London

Machine Learning & Data Analytics

Note

These the machine learning projects and articles on data analytics that I have written. Code for the projects can be found in an attachment section at the top of each articles.

  • Random Forest Doesn’t (Does) Overfit

Link to Article

  • Analyzing Hepatitis Survival With a Decision Tree

Link to Article


  • Simple Linear Regression

Part 1 - Mathematical Theory  |  Part 2 - Estimating Yacht Hydrodynamics  |  Part 3 - GDP and Life Expectancy


  • Labeling Recipes with Logistic Regression

Part 1 - Mathematical Theory  |  Part 2 - Data Cleaning, Multicollinearity, and Recipe Labels


  • Naive Bayes

Part 1 - Mathematical Theory


  • Feedforward Neural Networks

Part 1 - The Perceptron


Mathematics & Statistics

Note

These articles are still mostly focused on machine learning and statistics but are more on the theoretical side or more research focused. There is also the occasional

  • Bias and Variance, in Statistics and Machine Learning

Part 1 - Bias and Variance in Statistics  |  Part 2 - Bias and Variance in Machine Learning


  • When Not To Use Bayesian Probability Estimation

Link to Article


  • Great Papers in Statistics & Machine Learning

Link to Article


  • The No Free Lunch Theorems

Link to Article


  • The Axiom of Choice

Link to Article