Unsupervised Learning from Skillsoft

Online, Self-Paced

Unsupervised learning can provide powerful insights on data without the need to annotate examples. In this course, you will learn several different techniques in machine learning.

Learning Objectives

Introducing Unsupervised Learning

start the course
describe unsupervised learning and some of the problems it can solve

Rule Association

describe rule association and how the apriori algorithm performs this task
use the apriori algorithm for rule association in Python

Cluster Analysis

describe clustering and the types of problems it applies to
describe the k-means clustering algorithm
use SciKit Learn to build clusters in python

Anomaly Detection

describe anomaly detection, the types of problems solved with anomaly detection, and some approaches to anomaly detection
use scikit learn to perform anomaly detection

Dimensionality Reduction

describe the problems with dimensionality and why efforts to reduce dimensionality should be taken
describe principal component analysis for dimensionality reduction
use SciKit Learn to perform dimensionality reduction

Practice: Unsupervised Learning