How to Assess Model Fit in Machine Learning
An Easy Guide to K-Fold Cross-Validation
To evaluate the performance of some model on a dataset, we need to measure how well the predictions made by the model match the...
How to Assess Model Fit in Machine Learning
A Quick Intro to Leave-One-Out Cross-Validation (LOOCV)
To evaluate the performance of a model on a dataset, we need to measure how well the predictions made by the model match the...
Classification in Machine Learning
Introduction to Quadratic Discriminant Analysis
When we have a set of predictor variables and we’d like to classify a response variable into one of two classes, we typically use...
Classification in Machine Learning
Introduction to Linear Discriminant Analysis
When we have a set of predictor variables and we’d like to classify a response variable into one of two classes, we typically use...
Introduction to Machine Learning
What is the Bias-Variance Tradeoff in Machine Learning?
To evaluate the performance of a model on a dataset, we need to measure how well the model predictions match the observed data.
For regression...
Introduction to Machine Learning
Regression vs. Classification: What’s the Difference?
Machine learning algorithms can be broken down into two distinct types: supervised and unsupervised learning algorithms.
Supervised learning algorithms can be further classified into two...
Introduction to Machine Learning
A Quick Introduction to Supervised vs. Unsupervised Learning
The field of machine learning contains a massive set of algorithms that can be used for understanding data. These algorithms can be classified into...
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