Day 40: Clustering
A clustering algorithm looks at a number of data points and automatically finds data points that are related or similar to each other. In...
top of page
Joan Kusuma
Jan 33 min read
Day 39: Tree Ensembles
Using Multiple Decision Trees One of the weaknesses of using a single decision tree is that decision tree can be highly sensitive to...
Jan 22 min read
Day 38: Categorical and Continuous valued features
One Hot Encoding for Categorical Features In the examples we have seen so far, each of the features could take on only one of two...
Dec 29, 20233 min read
Day 37: Choosing a split: Information Gain
When building a decision tree, the way we will decide what feature to split on at a node will be based on what choice of feature reduces...
Nov 15, 20233 min read
Day 36: Decision Trees
In this section, we will learn about a practical and very commonly used learning algorithm: the decision tree. We will also learn about...
bottom of page