Playground for implementing and testing various deep learning models using PyTorch.
Jupyter Notebook for tensor can be accessed from notebooks/1.0-ant-tensor.ipynb
Jupyter Notebook for autograd can be accessed from: notebooks/2.0-ant-autograd.ipynb
Exploratory Data Analysis (EDA) for loan dataset can be accessed from: notebooks/3.0-eda.ipynb
For neural network with PyTorch can be accessed from: notebooks/4.0-torch_model.ipynb
For classical linear regression can be accessed from: notebooks/5.0-ant-classical-model-linear.ipynb
The codes to auto-generate sets of dataset files can be accessed from: scripts/generate_dataset.py
The codes for custom dataset class can be accessed from: scripts/custom_dataset.py
For Dashboard visualization: dash_board.py
Entry point for the whole project is main.py
Run tensorboard with: tensorboard --logdir=runs
For pip use: pip install -r requirements.txt
For conda use: conda env create -f environment.yml