UNSUPERVISED LEARNING

1. 1Explore the concept of unsupervised learning using online resources like scikit-learn documentation
2. 2Apply K-Means clustering algorithm to a sample dataset using Python
3. 3Visualize the results of unsupervised learning using dimensionality reduction techniques like PCA or t-SNE
4. 4Compare the performance of different unsupervised learning algorithms like Hierarchical Clustering and DBSCAN
5. 5Build a simple unsupervised learning model using a library like TensorFlow or PyTorch

Data scientists and machine learning engineers can benefit from understanding unsupervised learning to improve their skills in handling unlabeled data

💡 Unsupervised learning helps identify hidden patterns and relationships in unlabeled data

🤖 Unsupervised learning: discover patterns in unlabeled data! #MachineLearning #UnsupervisedLearning