Unsupervised Machine Learning

IBM via Coursera

Intermediate

Online

7 Weeks

particular

details

                                    Medium of instructions
                                    English

                                    Mode of learning
                                    Self study

                                    Mode of Delivery
                                    Video and Text Based

Module 1: Introduction to Unsupervised Learning and K Means

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

Readings

K Means Demo (Activity)
Summary

Assignments

Introduction to Unsupervised Learning
K Means Clustering
End of Module

App items

K Means Demo (Activity)
Practice Lab: K Means Clustering Lab
Practice Lab: Mixture of Gaussians Lab

Module 2: Selecting a clustering algorithm

Videos

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

Readings

Curse of Dimensionality Demo (Activity)
Clustering Demo (Activity)
Summary

Assignments

Distance Metrics
Clustering Algorithms
Comparing Clustering Algorithms
End of Module

App items

Demo lab: Curse of Dimensionality
Practice Lab: Distance Metrics Lab

Module 3: Dimensionality Reduction

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

Readings

Principal Component Analysis (Activity)
Non Negative Matrix Factorization (Activity)
Summary

Assignments

Dimensionality Reduction
Non Negative Matrix Factorization
End of Module

App items

Practice lab: DBSCAN Clustering
Practice lab: Mean Shift Clustering
Clustering Demo (Activity)

Module 4: Dimensionality Reduction

Videos

Dimensionality Reduction: Overview
Dimensionality Reduction: Principal Component Analysis
(Optional) Dimensionality Reduction Notebook - Part 1
Dimensionality Reduction Notebook - Part 2
Dimensionality Reduction Imaging Example

Reading

Summary

Assignments

Graded: Module 4 Quiz
Ungraded: Dimensionality Reduction

App items

(Optional) Matrix Review
Demo lab: Dimensionality Reduction (Part 1)
Practice lab: Principal Component Analysis
Singular Value Decomposition

Module 5: Nonlinear and Distance-Based Dimensionality Reduction

Videos

Kernel Principal Component Analysis and Multidimensional Scaling
Dimensionality Reduction Notebook - Part 3

Reading

Summary

Assignments

Graded: Module 5 Quiz
Ungraded: Kernel PCA and MDS

App items

Demo lab: Dimensionality Reduction (Part 2)
Practice lab: Kernel PCA•45 minutes
Practice lab: Multidimensional Scaling

Module 6: Matrix factorization

Videos

Non Negative Matrix Factorization
Non Negative Matrix Factorization Notebook - Part 1
Non Negative Matrix Factorization Notebook - Part 2

Reading

Summary

Assignments

Graded: Module 6 Quiz
Ungraded: Non Negative Matrix Factorization

App items

Demo lab: Non-Negative Matrix Factorization
(Optional) TF-IDF Supplemental
Practice lab: Non-Negative Matrix Factorization

Module 7: Final Project

Peer review

Course Final Project

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Unsupervised Machine Learning

Intermediate

Online

7 Weeks

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The syllabus

Module 1: Introduction to Unsupervised Learning and K Means

Videos

Readings

Assignments

App items

Module 2: Selecting a clustering algorithm

Videos

Readings

Assignments

App items

Module 3: Dimensionality Reduction

Videos

Readings

Assignments

App items

Module 4: Dimensionality Reduction

Videos

Reading

Assignments

App items

Module 5: Nonlinear and Distance-Based Dimensionality Reduction

Videos

Reading

Assignments

App items

Module 6: Matrix factorization

Videos

Reading

Assignments

App items

Module 7: Final Project

Peer review

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