Abhishek-Mallick / Abhishek-Mallick/universal-box
[TEMPLATE] – Image Recognition Using CNNs - DataScience
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- JavaScript
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Beschreibung
### What domain will the project template be based on?
Data Science
### If 'Others', please specify the preferred domain.
_No response_
### Particular directory path for the template.
`templates/Data Science/Classifications/ImageRecognitionCNN`
### What tech stacks do you want to include?
Python, TensorFlow, Keras
### Brief Description
A project template that uses Convolutional Neural Networks (CNNs) to classify images into categories.
Reference(implementation like) : [teachablemachine](https://teachablemachine.withgoogle.com/)
**Note :** A Jupyter notebook in form of a collab notebook should be linked in the README.md, and a user-friendly UI should be built using Flask or Streamlit.
### 👀 Have you spent some time checking if this issue has been raised before?
- [X] Yes
- [ ] No
### 🏢 Have you read the Code of Conduct?
- [X] I have read the [Code of Conduct](https://github.com/Abhishek-Mallick/universal-box/blob/main/.github/CODE_OF_CONDUCT.md)
### Would you like to work on this issue?
No
Beitragsleitfaden
Rechercherichtung
Create a project template in templates/Data Science/Classifications/ImageRecognitionCNN. Include a CNN model for image classification using TensorFlow/Keras. Provide a Jupyter notebook (linked in README) and build a user-friendly UI with Flask or Streamlit. Reference TeachableMachine for implementation ideas. Ensure the template is structured for one-click deployment via Universal-Box.
Vom Indexierungsmodell aus dem Issue-Text verfasst.
Bewertung
- Tech-Stack
- flask, jupyter, jupyter-notebook, keras, python, streamlit, tensorflow
- Bereich
- ai, data, machine-learning, web-dev
- Issue-Typ
- Feature
- Schwierigkeit
- 4/5
- Geschätzter Aufwand
- 3-5 Tage
- Aktivitätsstatus
- Veraltet
- Klarheit
- Größtenteils klar
- Anfängerfreundlichkeit
- 45/100