Unsupervised Machine Learning

IBM via Coursera

Intermediate

Online

2 Weeks

particular

details

                                    Medium of instructions
                                    English

                                    Mode of learning
                                    Self study

                                    Mode of Delivery
                                    Video and Text Based

                                    Learning efforts
                                    10 Hours Per Week
                                

Videos

Course Introduction
Introduction to Unsupervised Learning - Part 1
Introduction to Unsupervised Learning - Part 2
Introduction to Clustering
K-Means - Part 1
K-Means - Part 2
K-Means - Part 3
K-Means - Part 4
K Means Notebook - Part 1
K Means Notebook - Part 2
K Means Notebook - Part 3

Distance Metrics - Part 1
Distance Metrics - Part 2
Curse of Dimensionality Notebook - Part 1
Curse of Dimensionality Notebook - Part 2
Curse of Dimensionality Notebook - Part 3
Curse of Dimensionality Notebook - Part 4
Hierarchical Agglomerative Clustering - Part 1
Hierarchical Agglomerative Clustering - Part 2
DBSCAN - Part 1
DBSCAN - Part 2
Mean Shift
Comparing Algorithms
Clustering Notebook - Part 1
Clustering Notebook - Part 2
Clustering Notebook - Part 3
Clustering Notebook - Part 4

Videos

Dimensionality Reduction - Part 1
Dimensionality Reduction - Part 2
PCA Notebook - Part 1
PCA Notebook - Part 2
PCA Notebook - Part 3
Non-Negative Matrix Factorization
Non Negative Matrix Factorization Notebook - Part 1
Non Negative Matrix Factorization Notebook - Part 2
Dimensionality Reduction Imaging Example

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Unsupervised Machine Learning

Intermediate

Online

2 Weeks

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The syllabus

Module 1: Introduction to Unsupervised Learning and K Means

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Practice Exercises

Module 2: Selecting a clustering algorithm

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Practice Exercises

Module 3: Dimensionality Reduction

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