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https://github.com/pro-2684/pr-ml

Ground-up implementations of neural network and SVM for classifying MNIST dataset
https://github.com/pro-2684/pr-ml

algebra algorithm mnist multiclass-classification neural-network rust svm

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Ground-up implementations of neural network and SVM for classifying MNIST dataset

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# pr-ml

[![GitHub License](https://img.shields.io/github/license/PRO-2684/pr-ml?logo=opensourceinitiative)](https://github.com/PRO-2684/pr-ml/blob/main/LICENSE)
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[![GitHub Release](https://img.shields.io/github/v/release/PRO-2684/pr-ml?logo=githubactions)](https://github.com/PRO-2684/pr-ml/releases)
[![GitHub Downloads (all assets, all releases)](https://img.shields.io/github/downloads/PRO-2684/pr-ml/total?logo=github)](https://github.com/PRO-2684/pr-ml/releases)
[![Crates.io Version](https://img.shields.io/crates/v/pr-ml?logo=rust)](https://crates.io/crates/pr-ml)
[![Crates.io Total Downloads](https://img.shields.io/crates/d/pr-ml?logo=rust)](https://crates.io/crates/pr-ml)
[![docs.rs](https://img.shields.io/docsrs/pr-ml?logo=rust)](https://docs.rs/pr-ml)

> [!NOTE]
> This project is primarily used as my handin for Pattern Recognition & Machine Learning course.

Ground-up implementations of the following methods for classifying MNIST dataset:

- [x] Neural Network
- [x] Linear SVM
- [x] Kernel SVM

## 📥 Installation

### Using [`binstall`](https://github.com/cargo-bins/cargo-binstall)

```shell
cargo binstall pr-ml
```

### Downloading from Releases

Navigate to the [Releases page](https://github.com/PRO-2684/pr-ml/releases) and download respective binary for your platform. Make sure to give it execute permissions.

### Compiling from Source

```shell
cargo install pr-ml
```

## 💡 Examples

TODO

## 📖 Usage

TODO

## 🎉 Credits

- [Backpropagation, intuitively | Deep Learning Chapter 3](https://www.youtube.com/watch?v=Ilg3gGewQ5U)
- [Backpropagation calculus | Deep Learning Chapter 4](https://www.youtube.com/watch?v=tIeHLnjs5U8)
- [`nalgebra` - Linear algebra library for Rust](https://www.nalgebra.rs/)
- [Support vector machine - Wikiwand](https://www.wikiwand.com/en/articles/Support_vector_machine)
- [Learning: Support Vector Machines](https://www.youtube.com/watch?v=_PwhiWxHK8o)