World-of-AI
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adithya-s-k
Mushroom Classification
Project Request
In this mushroom classification problem, the objective is to create a robust machine-learning model that can accurately determine the edibility of a mushroom-based on its binary attributes. The model should be trained on a comprehensive dataset containing information about different mushroom species and their corresponding labels of being edible or poisonous. The classification model will enable users to make informed decisions about consuming mushrooms while ensuring their safety.The model will be fully deployed using flask.
| Field | Description |
|---|---|
| About | This project aims to develop a machine-learning model that can accurately classify mushrooms as edible or poisonous based on their binary attributes. |
| Github | Atharva-Malode |
| [email protected] | |
| Label | Machhine-Learning, Decision Tree |
https://github.com/Atharva-Malode
Define You
- [ x] GSSOC Participant
Mushroom Classification
Description
This project aims to develop a machine-learning model to classify mushrooms as edible or poisonous based on binary attributes. The expected outcome is an accurate tool for identifying safe-to-consume mushrooms, benefiting individuals and promoting safer mushroom consumption practices.
Scope
This project aims to develop a machine-learning model for mushroom classification, with the objective of accurately distinguishing between edible and poisonous mushrooms based on binary attributes. The deliverables include a trained model and accompanying documentation, while constraints involve the availability of a comprehensive dataset and limited computational resources.
Timeline
The Project will be submitted within 2-3 days of assigning. It will be deployed using Flask.
