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Machine Learning

Machine Learning #2

Unsupervised Learning

Uchechukwu Emmanuel
Mar 8, 2022
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Machine Learning #2

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Unsupervised Learning

In unsupervised learning, each data point in the dataset is not defined; the algorithm is given unlabeled data with the goal of finding a structure. when a structure is found in the dataset, they are put into clusters

Clustering Algorithm

Cluster analysis, or clustering, is an unsupervised learning task. It involves automatically discovering natural grouping in data.

Clustering algorithms interpret the input data and find natural groups or clusters in the feature space.

Applications of Unsupervised Learning

  1. Google News: Google goes on the web and searches for hundreds of thousands of news articles and groups them into cohesive news stories.

  2. Genomics(DNA Microarray Data): Given a group of different individuals, a clustering algorithm can be used to measure how much they do or do not have a certain gene, and create clusters based on the pattern.

Other Examples

  • Organizing computer clusters in a data center

  • Social Network Analysis

  • Market Segmentation

  • Astronomical Data Analysis

The Cocktail Party Problem

Two people are talking at a cocktail party, Let's assume there are two microphones somewhere in the room at different distances, if recordings are taken from the two microphones, a clustering algorithm can be used to separate each person’s voice from the recording.

NEXT LECTURE: MODEL REPRESENTATION
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