ML

 

Module 1: Introduction to Unsupervised Learning

Module 2: K-Means Algorithm

Module 3: Expectation - Maximization Algorithm

Module 4: Hierarchical Clustering Algorithms

Module 5: Density Based Clustering Algorithms

Module 6: Quality of Clustering

Module 7: Association Rule Mining

Module 8: Hidden Markov Model

 Module 1: Introduction to Unsupervised Learning

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  Introduction to Unsupervised Learning
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  Common Approaches to Clustering
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  Some notes on the demonstrations

Module 2: K-Means Algorithm

 Module 2: K-Means Algorithm

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  K-Means - Getting Started
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  K-Means Algorithm
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  Convergence & Performance Aspects
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  K-Means Python Code
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  Choosing Number (K) of Clusters
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  K-Means Algorithm : Some Enhancements
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  K-Means Algorithm : Online Version (with sequential update)
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  Mini-batch K-Means Algorithm
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  K-Means Algorithm & Outliers

Module 3: Expectation - Maximization Algorithm

 Module 3: Expectation - Maximization Algorithm

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  Introduction
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  What is Mixtures of Gaussian?
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  Clustering as finding ML parameters for MoG
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  Expectation Maximization Algorithm - Initial Formulation
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  Expectation Maximization Algorithm - A General Formulation
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  EM Algorithm and K-Means Algorithm - Connection
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  Closing Points on EM Algorithm

Module 4: Hierarchical Clustering Algorithms

 Module 4: Hierarchical Clustering Algorithms

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  Hierarchical Clustering Algorithms - Introduction
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  What are Divisive & Agglomerative Clustering Algorithms ?
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  Single Linkage Clustering
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  Complete Linkage Clustering
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  Mean and Average Linkage Clustering

Module 5: Density Based Clustering Algorithms

 Module 5: Density Based Clustering Algorithms

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  Introduction to Density Based Clustering
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  DBSCAN - Understanding Terminologies - Part I
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  DBSCAN - Understanding Terminologies - Part II
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  DBSCAN Algorithm
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  DBSCAN Algorithm - Some Points

Industry Talk

 Industry Talk

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  Industry Talk 1
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  Industry Talk 2
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  Industry Talk 3

Module 6: Quality of Clustering

 Module 6: Quality of Clustering

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  Evaluation of Clustering - Introduction
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  Silhouette Method
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  Rand Index, Purity

Module 7: Association Rule Mining

 Module 7: Association Rule Mining

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  Market Basket Analysis
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  Terminology & Measures
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  Computational Complexity
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  Association Mining Rule Algorithm
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  Rule Generation
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  Efficiency of Association Mining Algorithm
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  Evaluating the interestingness of patterns

Module 8: Hidden Markov Model

 Module 8: Hidden Markov Model

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  States and Observations
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  Transition Model
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  Sensor Model
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  Hidden Markov Models
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  State Estimation Problem
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  Illustrating Filtering with an example
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  Prediction with HMM
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  Smoothing with HMM
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  Viterbi Algorithm

Course Handout

 Course Handout

• Attachment

  Unsupervised Learning & Association Rule Mining - for Canvas - Handout.pdf

Textbooks

 Textbooks

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  artificial-intelligence-Rusell and Norveg.pdf
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  Bishop - Pattern Recognition And Machine Learning - Springer 2006.pdf
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  The-Morgan-Kaufmann-Series-in-Data-Management-Systems-Jiawei-Han-Micheline-Kamber-Jian-Pei-Data-Mining.-Concepts-and-Techniques-3rd-Edition-Morgan-Kaufmann-2011 (1).pdf

Webinar/ Lab Files

 Webinar/ Lab Files

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  K-means Implementation using make_moon.ipynb
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  K-means Implementation.ipynb
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  Association Rule Mining.ipynb
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  POS Tagging using HMM-AIML-Course-4.ipynb

Immersion 2 Documents - As received from the speakers & Capstone Documents

 Immersion 2 Documents - As received from the speakers & Capstone Documents

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  C5 Text Mining AIML Cohort 10 Immersion by Dr. Chetana Gavankar.pdf
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  C6 Deep Learning AIML Cohort 10 Immersion.pdf
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  Text Mining Industrial Usecase.pdf
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  AIML Capstone - Project Report Template - Student Reference-Canvas.docx
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  Cohort 10 - C7 - Capstone Project v3.0 - ML & AI - Handout.docx

Session Slides/Study Material

 Session Slides/Study Material

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  Session 1.ppt
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  Introduction to Unsupervised Learning and K-means
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  Session 2.ppt
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  K-means Implementation.ipynb
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  Dataset-WineKMC .xlsx
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  k-means and its variants
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  Session - 3 GMM using EM
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  K-means Implementation using make_moon.ipynb
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  Session - 4 Hierarchical Clustering 28th April 2024.pdf
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  Hierarchical Clustering (Except Result Interpretation).py
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  WineKMC .xlsx
• Context Module Subheader

  Session - 5
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  Contact Session 5 - Density Based Clustering.pdf
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  Density Based Clustering .py
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  Cluster Validation
• Context Module Subheader

  Session - 6
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  Contact Session - 6 Association Rule Mining.pdf
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  Association Rule Mining.ipynb
• Context Module Subheader

  Session - 7
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  Contact Session - 7 Hidden Morkov Model.pdf
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  POS Tagging using HMM-AIML-Course-4.ipynb