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DA📍Unsupervised Machine Learning Algorithms (Episode 76 of 100): DM to Download the free PDF👇
1. Unsupervised learning is a type of machine learning that analyzes unlabeled data to find patterns and relationships. It’s also known as unsupervised machine learning.
2. How it works?
✅ An algorithm is given unlabeled data
✅ The algorithm identifies patterns and relationships in the data without human intervention
✅ The algorithm uses the patterns to recognize new input data
3. What it’s used for?
✅ Exploratory data analysis: Unsupervised learning can find similarities and differences in data
✅ Cross-selling strategies: Unsupervised learning can help identify customer purchasing patterns
✅ Customer segmentation: Unsupervised learning can help identify customer groups
✅ Image recognition: Unsupervised learning can help identify patterns in images
4. Types of unsupervised learning:
✅ Clustering: Divides data into groups based on similarities
✅ Dimensionality reduction: Reduces the number of variables considered in a problem
✅ Association rule learning: Finds relationships between features in a dataset
5. Some algorithms used in unsupervised learning include:
✅ PCA, t-SNE, UMAP, Apriori, Eclat, and FP-growth.
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