Basic Clustering for Complex Shapes
Explore the Gaussian Mixture, DBSCAN, Spectral Clustering, and KMeans algorithms. Learn how to evaluate and optimize them using Grid Search. Understand how the shape of the data and evaluation metrics influence their performance.
JetBrains Academy
About
As a Data Scientist, there may be times when you need to find patterns in data without any pre-defined labels. This represents an unsupervised machine learning problem. While many techniques exist to address this issue, clustering is a common starting point. In this project, you will work on training and optimizing different clustering algorithms using various types of data. You will discover that there is no one-size-fits-all algorithm for clustering, and the best choice depends on the data shape and the evaluation method.
Graduate project
This project covers the core topics of the Machine Learning with Python course, making it sufficiently challenging to be a proud addition to your portfolio.
At least one graduate project is required to complete the course.