Month: Jun 2021

This post aims to share my Machine Learning notebooks. There are three types of Machine Learning for predicting structured tabular data: (1) supervised learning, (2) unsupervised learning, and (3) reinforcement learning. A supervised learning objective is to build a prediction model from a training dataset to predict an unseen test dataset. Supervised learning can solve regression tasks (for continuous output) and classification tasks (for categorical output). Unsupervised learning aims to learn the dataset patterns to simplify the information by clustering and dimensionality reduction. Cluster analysis groups observations into some clusters according to the similarity of their features. Dimensionality reduction reduces the number of dataset dimensions or features. Previously, I have written a post on basic Machine Learning here.