/Supervised-Learning-Workshop

Primary LanguageJupyter Notebook

Supervised-Learning-Workshop

This repository contains the materials for the two sessions on Supervised Learning WTM Summer Bootcamp. The materials include PDF slides and a notebook used during the sessions.

Content

Session 1: Introduction to Supervised Learning

  • Slides: Supervised Learning 1
  • Topics Covered:
    • Introduction to Supervised and Unsupervised Learning
    • Types of Supervised Learning (Classification, Regression)
    • Important Concepts: Target and Descriptive Features
    • Common Algorithms: k-Nearest Neighbors, Naive Bayes, Decision Trees, and Random Forests

Session 2: Advanced Topics in Supervised Learning

  • Slides: Supervised Learning 2
  • Topics Covered:
    • Decision Trees and Hunt’s Algorithm
    • Support Vector Machines (SVM)
    • Logistic and Linear Regression
    • Evaluation Metrics: Accuracy, Confusion Matrix, and Handling Imbalanced Datasets