Unsupervised Machine Learning with 2 Capstone ML Projects
Learn Complete Unsupervised ML: Clustering Analysis and Dimensionality Reduction
What you'll learn
- Understand the Working of K Means, Hierarchical, and DBSCAN Clustering.
- Implement K Means, Hierarchical, and DBSCAN Clustering using Sklearn.
- Learn Evaluation Metrics for Clustering Analysis.
- Learn Techniques used for Treating Dimensionality.
- Implement Correlation Filtering, VIF, and Feature Selection.
- Implement PCA, LDA, and t-SNE for Dimensionality Reduction.
- Analyze the Climatic Factors Best to Grow Certain Crops.
- Recommend Crops by looking at Certain Climatic Factors.
- Categorize the data into n number of relevant groups which are useful for Marketing Purposes.
- Identify the Target Group of Customers.
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