The Project Manager Assistant is a comprehensive solution for streamlining project management processes. Leveraging Machine Learning algorithms and advanced document processing techniques, this project aims to enhance decision-making, optimize resource allocation, and improve project outcomes across various industries.
- Machine Learning-driven Priority Prediction: Utilizes ML algorithms to accurately predict project priorities, aiding in effective resource allocation and task prioritization.
- PDF Document Processing: Efficiently processes PDF documents, segregating data into actionable statuses (pass, fail, undefined) with color-coded visualization for easy interpretation.
- User-friendly Interface: Incorporates a Tkinter GUI to provide a seamless and intuitive user experience, enhancing accessibility and usability.
- Machine Learning Priority Prediction: Implement machine learning algorithms to predict project priorities based on historical data and relevant features.
- PDF Document Processing: Develop mechanisms to extract structured data from PDF documents and categorize them into actionable statuses.
- GUI Development: Design and implement a user-friendly interface using Tkinter to facilitate easy interaction and visualization of project statuses.
- Python
- Machine Learning (scikit-learn)
- Document Processing (Tabula)
- GUI Development (Tkinter)
- Python 3.x installed
- Basic understanding of machine learning concepts
- Familiarity with Python programming language
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Clone the repository:
git clone https://github.com/Priyanshuparth/Project-Manager-Assitant.git
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Install the required dependencies:
pip install -r requirements.txt
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Run the
main.py
file:python main.py
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Follow the prompts to upload PDF documents and analyze project priorities and statuses.
Contributions are welcome! If you find any issues or have suggestions for improvement, feel free to open an issue or submit a pull request.
This project is licensed under the MIT License.
Project Management Assistant Home
Priority Check
Status Check