https://github.com/debjyotisaha/deep-learning-projects-phase-1
Deep Learning Projects which demonstrate the use of Python and its complex ML algorithms
https://github.com/debjyotisaha/deep-learning-projects-phase-1
deep-learning machine-learning neural-network numpy opencv pandas python seaborn streamlit
Last synced: 7 months ago
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Deep Learning Projects which demonstrate the use of Python and its complex ML algorithms
- Host: GitHub
- URL: https://github.com/debjyotisaha/deep-learning-projects-phase-1
- Owner: DebjyotiSaha
- Created: 2021-07-17T06:45:18.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2024-11-20T06:43:10.000Z (about 1 year ago)
- Last Synced: 2025-06-15T22:06:35.755Z (8 months ago)
- Topics: deep-learning, machine-learning, neural-network, numpy, opencv, pandas, python, seaborn, streamlit
- Language: Jupyter Notebook
- Homepage:
- Size: 890 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Deep Learning Projects - Phase 1
This repository contains deep learning projects built using Python and various deep learning libraries. These projects showcase applications in image detection and sound classification.
## Projects Included:
1. **Sound Classification**
- A model to classify sounds based on training data.
2. **Image Detection**
- Includes multiple components:
- `myWebApp`: Web application to interact with image detection models.
- `templates`: Templates for web app.
- `imgUpload`: A directory for uploading images.
## Requirements:
Ensure that you have the following libraries installed:
- Numpy
- Pandas
- Streamlit
- Cufflinks
- Sklearn
- Seaborn
- Matplotlib
- OpenCV (For image processing tasks)
## Installation Instructions:
1. Clone the repository:
```
git clone https://github.com/DebjyotiSaha/Deep-Learning-Projects-Phase-1.git
```
2. Install required libraries:
```
pip install -r requirements.txt
```
3. For image detection tasks, you may want to use **Google Colab** or any IDE that supports OpenCV.
## Usage:
- **Sound Classification**: Follow the instructions in the notebook to train and test the model on sound data.
- **Image Detection**: Launch the web app (`myWebApp`) to upload and classify images.
## License:
This project is licensed under the MIT License - see the LICENSE file for details.