ASCI-COEP / ASCI-COEP/Kaggle-Competitions
Build a classification model for Bengali handwritten digits
- Dominant language
- Jupyter Notebook
- Stars
- 2
- Forks
- 4
- PR merge metrics
- No merged PRs in 30d
Description
**Bengali Handwritten Digit Recognition**
In this competition, your goal is to correctly identify digits from NumtaDB.
[This ](https://www.kaggle.com/c/numta)is the kaggle link where you will find the relevant dataset. Also, it will help you to understand the problem statement more clearly.
Contributor guide
No contributing guide indexed for this repository
Research direction
Start with the NumtaDB Kaggle competition linked in the issue and read its problem statement and dataset details. Determine how the Bengali handwritten digit data should be used to train and evaluate a classification model. Done means a reproducible model or notebook that correctly identifies the competition's digit classes, but the issue provides no repository files, tests, or target metric.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, machine-learning
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100