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Topic Modeling. How do we identify topics within a corpus of documents? In this part, we study unsupervised learning of text data. Specifically, we use topic models such as Latent Dirichlet Allocation and Non-negative Matrix Factorization to construct “topics” in text from the statistical regularities in the data.
Prerequisites: Python Text Analysis Fundamentals: Parts 1-2
Workshop Materials: https://github.com/dlab-berkeley/Python-Text-Analysis
Software Requirements: Installation Instructions for Python Anaconda
Is Python Not working on your laptop? Attend the workshop anyway, we can provide you with a cloud-based solution until you figure out the problems with your local installation.
onlFeedback: After completing the workshop, please provide us feedback using this form