Topic Modeling and Clustering focuses on discovering hidden patterns and grouping similar data points in large datasets, especially text data. It enables organizations to automatically identify themes, structures, and relationships without predefined labels. This training explains topic modeling techniques such as Latent Dirichlet Allocation (LDA) and Non-negative Matrix Factorization (NMF). It also covers clustering methods like K-Means, hierarchical clustering, and density-based algorithms. You will learn how these techniques are used in text analytics, customer segmentation, and document classification. The course also highlights best practices for improving model accuracy and interpreting results effectively.
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