Unsupervised Machine Learning with 2 Capstone ML Projects
Learn Complete Unsupervised ML: Clustering Analysis and Dimensionality Reduction
What you’ll learn
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Understand the Working of K Means, Hierarchical, and DBSCAN Clustering.
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Implement K Means, Hierarchical, and DBSCAN Clustering using Sklearn.
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Learn Evaluation Metrics for Clustering Analysis.
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Learn Techniques used for Treating Dimensionality.
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Implement Correlation Filtering, VIF, and Feature Selection.
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Implement PCA, LDA, and t-SNE for Dimensionality Reduction.
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Analyze the Climatic Factors Best to Grow Certain Crops.
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Recommend Crops by looking at Certain Climatic Factors.
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Categorize the data into n number of relevant groups which are useful for Marketing Purposes.
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Identify the Target Group of Customers.
Who this course is for:
- Anyone who want to start a career in Unsupervised Machine Learning.
- Any people who want to level up their Unsupervised Machine Learning Knowledge.
- Software developers or programmers or Tech lover who want to change their career path to Unsupervised machine learning.
