https://github.com/bagusperdanay7/final-project-dicoding
My Dicoding final project, Rock-paper-scissors Image classification using Python & TensorFlow.
https://github.com/bagusperdanay7/final-project-dicoding
deep-learning image-classification machine-learning python tensorflow
Last synced: 3 months ago
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My Dicoding final project, Rock-paper-scissors Image classification using Python & TensorFlow.
- Host: GitHub
- URL: https://github.com/bagusperdanay7/final-project-dicoding
- Owner: bagusperdanay7
- License: mit
- Created: 2024-02-13T12:03:22.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2025-01-12T15:58:00.000Z (over 1 year ago)
- Last Synced: 2025-01-30T09:17:47.371Z (over 1 year ago)
- Topics: deep-learning, image-classification, machine-learning, python, tensorflow
- Language: Jupyter Notebook
- Homepage:
- Size: 762 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Rock-Paper-Scissors Image Classification
[**Dokumentasi Bahasa Indonesia (Indonesia Documentation)**](/docs/id/README.md)
A machine learning application built with Python and TensorFlow, implementing the Convolutional Neural Network algorithm to classify images of rock, scissors, and paper. This project is designed to aid in completing Dicoding Indonesia's Machine Learning for Beginners course.
## Technology stack & Tools
**This program needs:**
| Tech Stack & Tools | Version |
| ------------------- | ------- |
| Python | 3.8+ |
| Google Colaboratory | Latest |
| split-folders | 0.5+ |
| TensorFlow | 2.13+ |
| Numpy | 1.24+ |
| Matplotlib | 3.7+ |
## Setup (Google Colab)
### Clone the repository
Since this programme is run on Google Colab, open Google Colab.
[](https://colab.research.google.com/)
And then clone my repository:
```shell
git clone https://github.com/bagusperdanay7/final-project-dicoding.git
```
1. Open Google Colab
2. Select menu File > Open notebook > GitHub
3. Copy '' to the input box
4. Search and wait for the repository to load.
5. Select the repository that shows up.
6. And voila. Run the program.
7. Select Runtime > Run all
