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Blog Archives

A Gentle Introduction to Artificial Neural Networks

Posted by dustinstansbury

The material in this post has been migrated to a post by the same name on my github pages website.

Posted in Classification, Gradient Descent, Machine Learning, Neural Networks, Neuroscience, Regression

Tags: Backpropagation, Classification, Deep Learning, Gradient Descent, Neural Networks, Regression

Model Selection: Underfitting, Overfitting, and the Bias-Variance Tradeoff

Posted by dustinstansbury

The material in this post has been migrated with python implementations to my github pages website.

Posted in Regression, Simulations, Statistics, Theory

Tags: bias-variance decomposition, bias-variance tradeoff, dependent variable, estimator, estimator bias, estimator variance, independent variable, learning curve, polyfit.m, polynomial model, Regression, Simulation, testing error, testing set, training error, training set

Cutting Your Losses: Loss Functions & the Sum of Squares Loss

Posted by dustinstansbury

The material for this post has been migrated to my GitHub pages site. See you there!

Posted in Regression, Statistics, Theory

Tags: Least Squares, Linear Models, Loss Functions, Parameter Estimation, Regression

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