Supervised Learning Tutorials

Supervised learning is a fundamental concept in machine learning, where algorithms learn from labeled training data. This tutorial will cover the basics of supervised learning, including different types of algorithms and their applications.

Types of Supervised Learning

1. Regression

   • Linear Regression
   • Logistic Regression
   • Polynomial Regression
   • More on Regression

2. Classification

   • Decision Trees
   • Random Forest
   • Support Vector Machines (SVM)
   • More on Classification

3. Clustering

   • K-Means
   • Hierarchical Clustering
   • DBSCAN
   • More on Clustering

Applications of Supervised Learning

• Image Recognition
• Natural Language Processing
• Financial Modeling
• Healthcare

Key Concepts

• Training Data: Data used to train the model.
• Test Data: Data used to evaluate the model's performance.
• Validation Data: Data used to tune the model's hyperparameters.

Resources

• Machine Learning Crash Course by Google
• Supervised Learning with Python

Supervised Learning