Explore unsupervised learning techniques in this comprehensive video tutorial based on Chapter 9 of "Hands-on Machine Learning with Scikit-Learn, Keras & Tensorflow." Dive into key concepts such as clustering, dimensionality reduction, and semi-supervised learning. Learn to import and preprocess data, implement mini-batching, and evaluate clustering performance using silhouette scores and diagrams. Discover practical applications like image segmentation and gain insights into advanced topics including PCA, Gaussian Mixture Models, and Bayesian Gaussian Mixture Models. Follow along with code examples and visualizations to enhance your understanding of these powerful machine learning techniques.
Overview
Syllabus
Introduction
Unsupervised Learning
Import Data
Import Preprocessing
Graphing
Mini Batching
Silhouette Score
Cluster Distance
Silhouette Diagram
Image Segmentation
Dimensionality Reduction
Semisupervised Learning
PCA
Gaussian Mixture Models
Bayesian Gaussian Mixture Models
Taught by
Shashank Kalanithi
