Time series modelling - arima

Note on the ARIMA model for time series forecasting

Boosting part 1: introduction and adaboost

An introduction to the concept of boosting and a guide to the AdaBoost algorithm.

Decision trees

Introduction to decision trees, which form the basis for more sophisticated algorithms.

Linear regression with gradient descent

Deriving the gradient descent algorithm to fit a linear regression model and implementing it in Python

Logistic regression

Implementing a linear model for classification tasks in Python

Random forests

Ensemble machine learning algorithm consisting of multiple decision trees.

Regularised regression

Regularisation techniques to simplify models, in order to avoid overfitting and improve interpretability