Bias and Variance Introduction Machine learning models are developed primarily to produce good predictions for some desired quantity. What we want is a model that can generalise well the patterns in our data in order to make reasonable predictions. Two important measures of how well a model generalises are bias and variance: Bias is the tendency […]
Mean Absolute Error Introduction With any machine learning project, it is essential to measure the performance of the model. What we need is a metric to quantify the prediction error in a way that is easily understandable to an audience without a strong technical background. For regression problems, the Mean Absolute Error (MAE) is just such
Mean Absolute Error Read More »
Implement the Bootstrap Method in Python from Scratch In this post we will implement the Bootstrap Method, and use it to analyse a linear regression model. Through this exercise, we will understand how this technique works, and how you can apply the bootstrap method in Python from scratch. Note: for those who prefer video content,
Implement the Bootstrap Method in Python from Scratch Read More »