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IDS
General
Workflows and Exploratory Data Analysis
Hierarchical Clustering
Explaining Clusters
Outlier Detection, Silhouette Score and k-Means Clustering
Homework 1
Dimensionality Reduction with Principal Components Analysis
Data embedding: MDS and t-SNE
Homework 2
Introduction to Classification, Overfitting, and Evaluation of Predictive Accuracy
Classifiers
Homework 3
Feature Subset Selection
Scoring of Classification Models
Working with Unstructured Data
Homework 4
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Introduction to Data Science
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IDS
Homework 1
Assignment 1: Exploratory Analysis and Clustering
Assignment 1: Exploratory Analysis and Clustering
◄ Exploratory data analysis
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Final Exam
Exploratory data analysis
Dimensionality reduction and explanations of the data maps
Classifiers and their Decision Boundaries
Image Analytics
Dimensionality reduction and explanations of the data maps ►