Assignment of Unsupervised Learning Algorithms

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Assignment of Unsupervised Learning Algorithms

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Sanket Tippe

Bezawada Bala Srikanth

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Course Content

Introduction to Machine Learning

Environment Setup part 1

Environment Setup part 2

Environment Setup part 3

Data Wrangling

Importing Libraries and Dataset

Handling Missing Data

Handling Missing Data - Practical

Encoding Categorical Data

Encoding Categorical Data - Practical

Splitting Dataset

Splitting Dataset - Practical

Normalizing the Data - Part 1

Normalizing the Data - Part2

Finding Machine Learning Datasets

Exploratory Data Analysis

Plotting Graphs - Part 1

Plotting Graphs - Part 2

Distribution Models - Part 1

Distribution Models - Part 2

Assignment of Data Preprocessing for Machine Learning

Machine Learning Paradigms

Sampling Methods

Underfitting and Overfitting in Models

Variance and Bias

Distance Metrics

K-Means Clustering

K-Means Clustering - Practical

Hierarchical Clustering - Agglomerative , Divisive

Agglomerative Clustering - Practical

Divisive Clustering - Practical

DBscan Spatial Clustering

FP Growth

Assignment of Unsupervised Learning Algorithms

Overview of Dimensionality Reduction

Principal Component Analysis

Princinpal Component Analysis - Practical

Linear Discriminant Analysis

Linear Discriminant Analysis - Practical

Assignment of Dimensionality Reduction

Advance Trends in Machine Learning

Course Summary

Interview Questions part 1

Interview Questions part 2

Interview Questions part 3

Career Guidelines