https://github.com/mananabbasi/machine-learning-and-data-mining-
This repository contains **Machine Learning** and **Data Mining** projects, where I explore datasets, build predictive models, and uncover patterns using techniques like **Classification**, **Clustering**, and **Sentiment Analysis and Text Mining**. Each project includes code, datasets, and detailed documentation to showcase the process and results
https://github.com/mananabbasi/machine-learning-and-data-mining-
anaconda business-analytics business-intelligence classification clustering data-science data-visualization jupyter-notebook machine-learning python sentiment-analysis text text-classification
Last synced: 1 day ago
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This repository contains **Machine Learning** and **Data Mining** projects, where I explore datasets, build predictive models, and uncover patterns using techniques like **Classification**, **Clustering**, and **Sentiment Analysis and Text Mining**. Each project includes code, datasets, and detailed documentation to showcase the process and results
- Host: GitHub
- URL: https://github.com/mananabbasi/machine-learning-and-data-mining-
- Owner: mananabbasi
- Created: 2024-10-16T12:40:26.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-01T22:46:50.000Z (over 1 year ago)
- Last Synced: 2025-05-17T11:11:07.327Z (about 1 year ago)
- Topics: anaconda, business-analytics, business-intelligence, classification, clustering, data-science, data-visualization, jupyter-notebook, machine-learning, python, sentiment-analysis, text, text-classification
- Language: Jupyter Notebook
- Homepage:
- Size: 8.87 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
This repository contains projects focused on Classification, Clustering, and Sentiment Analysis, implemented using Python and popular machine learning libraries like Scikit-learn, NLTK, and TensorFlow. Each project includes code, datasets, and detailed documentation to explore techniques such as predictive modeling, unsupervised learning, and text analysis. Whether you're analyzing customer sentiment, grouping data into clusters, or building classification models, these projects provide a practical guide to understanding and applying machine learning concepts. Feel free to explore, modify, and use the code for your own datasets! For questions, reach out via [Your Email] or [Your GitHub Profile]. Happy coding!