Applied Machine Learning with Python

This course offers an in-depth, practical introduction to machine learning using Python, covering core concepts across supervised, unsupervised, and semi-supervised methods. Through hands-on exercises, you will master key algorithms such as decision trees and random forests for classification, regression models for prediction, and K-means clustering to uncover patterns in unlabeled data. You will also learn how to implement model boosting techniques to enhance accuracy and apply strategies for effectively leveraging unlabeled data to improve performance. This course is designed for learne…