https://github.com/kkeshav1101/priority_encoder
A fullstack application mimicking a To-Do App but optimising it to improve productivity by predicting the relative importance of each task.
https://github.com/kkeshav1101/priority_encoder
bootstrap css django frontend fullstack-development html5 nlp-machine-learning python randomforestregressor
Last synced: 6 months ago
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A fullstack application mimicking a To-Do App but optimising it to improve productivity by predicting the relative importance of each task.
- Host: GitHub
- URL: https://github.com/kkeshav1101/priority_encoder
- Owner: KKeshav1101
- License: apache-2.0
- Created: 2024-01-19T17:25:04.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-12-08T13:23:10.000Z (10 months ago)
- Last Synced: 2025-03-25T06:41:41.423Z (7 months ago)
- Topics: bootstrap, css, django, frontend, fullstack-development, html5, nlp-machine-learning, python, randomforestregressor
- Language: Jupyter Notebook
- Homepage:
- Size: 226 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Priority_Encoder
> A fullstack application mimicking a To-Do App but optimising it to improve productivity by predicting the relative importance of each task.
> STATUS : Fully Functional Application now !!! Front-End Improvements incoming
Creators
Stack used
- python- pandas, tensorflow, scikit-learn, Django
- html, css, javascript, bootstrap
Workflow Diagram

Dataset Schema
- Task_id : primary_key int
- Account_Name : String
- Current_datetime : datetime
- Due_datetime : datetime
- Brief_Description : String
- Task_type : Category
- Hours_left : hrs in decimal (derived)
- Weight : int in range(10)(derived)
- Completed : boolean
Applications
- Workplace : Employer can efficiently assign tasks and ensure time is spent more appropriately on important tasks
- Academia : Can help with students' time management
- Should Increase Productivity and improve work life balance because an algorithm helps you decide where to start :) !
Scope for improvement
- The interface can be more friendly
- The dataset can be personalised better
Drawbacks
- Model will take time to give personalised predictions
- Too many input fields to enter may test your patience