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

Beitragsleitfaden öffnen

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

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