Basic Macine Learning and Deep Learning Models

This repository consists of some of the basic models used in ML/DL. It is constantly updated and the current list of model are listed below:

Models Included: Linear Regression | Linear Classification | Logistic Regression | Artificial Neural Networks (MNIST) | Convolution Neural Netorks (CIFAR10) | Convolution Neural Netorks (FashionMNIST)| Autoregressive Model

Tip

i) The trained model are saved in the models folders. For model structure used refere the code.
ii) The data folder might consists some data but its mainly used as an place-hodler for your own data

Setup the environment

1. Install UV (Package Manager)

2. Git colne the repo to your working directory:

git clone https://github.com/rohitDey23/deeplearning_models.git

3. Get into the cloned repository:

cd deeplearning_models

4. Initalize UV to recognize the project as uv project

uv init

5. Download all the required dependincies based on pyproject.toml file:

uv sync

If everything went well you wont see any error. To test if everything is working well run the following command.

uv run .\src\test_run.py 

This would print the version of python, numpy, pytorch. Also it should show if cuda device is available.

Caution

Note: Its expected to have a NVIDIA GPU for the project, manual adjustemnt in pyproject.toml would be needed for installing cpu version of putorch.