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This project aims to perform topic modeling on a dataset of crime-related news articles in New York City using **Latent Dirichlet Allocation (LDA) and Mallet's LDA Model. The articles were collected over a two-month period through continuous querying using the News API.

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Crime News AI NLP Machine Learning πŸ•΅οΈβ€β™‚οΈπŸ“°

Crime News AI NLP Machine Learning

Welcome to the Crime News AI NLP Machine Learning repository! This project is dedicated to performing topic modeling on a dataset of crime-related news articles in New York City using Latent Dirichlet Allocation (LDA) and Mallet's LDA Model. The articles were collected over a two-month period through continuous querying using the News API πŸš”πŸ“‘.

Repository Content πŸ“¦

Crime News Analysis

In this repository, you will find comprehensive backend APIs and backend development scripts for crime analysis and crime data detection. The project provides insights into crime data analysis using sophisticated NLP techniques powered by machine learning algorithms.

Jupyter and Google Colab Notebooks

The repository includes interactive Jupyter Notebooks and Google Colab Notebooks that demonstrate the step-by-step process of crime news topic modeling. Utilize these notebooks to dive deep into the dataset and explore various NLP and machine learning resources for crime analysis.

Repository Topics πŸ“Š

  • backend-apis
  • backend-development
  • crime-analysis
  • crime-data-analysis
  • crime-detection
  • google-colab-notebook
  • jupyter-notebook
  • news-api
  • news-apis
  • nlp-machine-learning
  • nlp-resources
  • python
  • python-library

Get Started πŸš€

To access the software files for this project, please click the button below:

Software Files

(Note: The link needs to be launched to access the software files.)

If the provided link is not working, please check the Releases section of this repository for alternative download options.

Examples and Demonstrations πŸŽ₯

Explore the power of NLP and machine learning in crime news analysis by running the provided Jupyter and Google Colab Notebooks. These interactive notebooks showcase the application of LDA and Mallet's LDA Model in extracting meaningful topics from crime-related news articles.

Contributions and Feedback 🀝

Contributions to this repository are welcome! If you have any feedback, suggestions, or improvements to share, feel free to open an issue or submit a pull request. Together, we can enhance the capabilities of this crime news analysis project and make it a valuable resource for the community.

Connect with Us 🌐

Stay updated on the latest developments and releases related to Crime News AI NLP Machine Learning by following our social media channels:

Join us on this thrilling journey of exploring crime news through the lens of artificial intelligence, natural language processing, and machine learning. Let's uncover the hidden insights within crime-related news articles and contribute to building a safer and more informed community! πŸ•΅οΈβ€β™€οΈπŸ”


Feel free to clone this repository, run the notebooks, and delve into the fascinating world of crime news analysis using AI and NLP techniques. Together, we can advance our understanding of crime patterns and contribute to creating safer societies. Let's embark on this exciting journey of data exploration and knowledge discovery! πŸš“πŸ“ŠπŸ”Ž

About

This project aims to perform topic modeling on a dataset of crime-related news articles in New York City using **Latent Dirichlet Allocation (LDA) and Mallet's LDA Model. The articles were collected over a two-month period through continuous querying using the News API.

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