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Module Overview

Learning Guides

3.1 Regression & Classification Methods

CAIEP - 3.1.1 Linear and Logistic Regression

CAIEP - 3.1.2 Decision Trees and Support Vector Machines

3.2 Unsupervised Learning

CAIEP - 3.2.1 Clustering in Unsupervised Learning

CAIEP - 3.2.2 Dimensionality Reduction

3.3 Model Evaluation

CAIEP - 3.3.1 Train/Test Split

CAIEP - 3.3.2 Cross-Validation: Mastering Model Evaluation

CAIEP - 3.3.3 Metrics for Model Evaluation

3.4 Implementation Tools

CAIEP - 3.4.1 Scikit-Learn

CAIEP - 3.4.2 Model Evaluation with Scikit-Learn Metrics

CAIEP - 3.4.3 Experimentation in Jupyter Notebooks

Recap Video

Module 3 - Recap Video

Applied Activities

Activities

Reflection Prompts

GitHub Instructions

GH CAiEP 3.1.1

GH CAiEP 3.3.3

Quiz

Quiz CAiEP 3.1

Quiz CAiEP 3.2

Quiz CAiEP 3.3

Quiz CAiEP 3.4

Quiz CAiEP 3.5

Quiz CAiEP 3.6

Quiz CAiEP 3.7

Quiz CAiEP 3.8

Module 3: Machine Learning Algorithms

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