Supervised and Unsupervised Learning

1. 1Read about supervised learning to understand how labeled data is used to train models
2. 2Explore unsupervised learning techniques to discover patterns in unlabeled data
3. 3Apply supervised learning using scikit-learn library in Python to classify images
4. 4Use K-means clustering algorithm for unsupervised learning to group similar data points
5. 5Compare the performance of supervised and unsupervised learning models on a sample dataset

Data scientists and machine learning engineers can benefit from understanding the fundamentals of supervised and unsupervised learning to build more accurate models

💡 Supervised learning uses labeled data, while unsupervised learning discovers patterns in unlabeled data

🤖 Supervised vs Unsupervised Learning: Know the difference to build better ML models!