Welcome to the a2DL
repository! This is your go-to source for advanced deep learning models, experiments, and utilities. Whether you're delving into research, studying, or just embarking on your deep learning journey, this repository aims to guide you further.
- Advanced Models: Dive deep into cutting-edge architectures and methodologies.
- Thorough Experiments: Gain insights into how different models behave under diverse scenarios.
- Utilities: Make use of handy functions and tools to make your workflow smoother.
For the experiments and models housed in this repository, please refer to the dataset here: Google Drive Dataset Link
Ensure to download and position the dataset correctly before executing the experiments.
git clone https://github.com/variyas31/a2DL.git
- Access the Google Drive Dataset Link to fetch the dataset.
- Extract and situate the dataset in the
data/
directory (or as indicated in the code).
- Ensure you have Python (version 3.6 or newer recommended).
- Jupyter Notebook is essential.
i. Set Up a Virtual Environment (Optional but advised)
This step helps in evading any potential conflicts with other projects or global packages:
```bash
python -m venv a2DL_env
source a2DL_env/bin/activate # On Windows, use `a2DL_env\Scripts\activate`
```
ii. Install Necessary Libraries
```bash
pip install pandas matplotlib seaborn tensorflow Pillow numpy scikit-learn keras-tuner jupyter IPython
```
iii. Kickstart Jupyter Notebook
```bash
jupyter notebook
```
This command opens the Jupyter interface in your default browser. From there, navigate to the `a2DL` repository's location and open the relevant notebooks.
Should you have any questions or feedback, kindly contact Variyas Nitin Singlaa.