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topicmodeling

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This project showcases an end-to-end workflow for topic modeling and text analysis using a variety of machine learning and natural language processing techniques. The goal of this project is to extract meaningful topics from a collection of text documents, enabling insights, categorization, and understanding of the underlying themes in the data.

  • Updated Sep 2, 2023
  • Jupyter Notebook
Text-Preprocessing-Vectorization-and-Classification-applying-NLP

We have performed a multi-class classification task of literary poems, which will be assigned to a period. Raw data has been collected from the web and processed the in order to apply Natural Language Processing and Machine Learning tools, such as feature extraction and selection, topic modeling, text preprocessing and classification

  • Updated Jun 4, 2024
  • Jupyter Notebook

Applied natural language processing (NLP) techniques to extract positive news for user-selected topics from online American news media. Topic modeling, classification modeling, and sentiment analysis were developed. A user interface was also created using Streamlit to output uplifting news for user-selected topics in the dataset.

  • Updated Aug 12, 2023
  • Jupyter Notebook

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