semvec/pypi-packages huggingface dataset:
baremetalml 1.0.0
Lightweight modular ML library from scratch in Python
License: MIT
Requires Python: >=3.8
Keywords: machine learning, ML, numpy, educational, baremetalml

# BareMetalML

**BareMetalML** is a lightweight, modular machine learning library built from scratch in Python by **Askari Abidi**.  
It is designed for **learning, experimentation, and educational purposes**, providing a clear and simple interface for core machine learning algorithms and preprocessing tools.  
All models and transformers are implemented using **pure NumPy**, making the library easy to understand and extend.

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## Features

### Easy and Modular Imports
BareMetalML allows **modular imports**, so you don’t need to worry about the internal file structure.  
For example, you can import any model or transformer like this:

```python
from baremetalml import LinearRegression, StandardScaler
```

No need to know which file the class is defined in — everything is ready to use.

## Core Models

**Linear Regression** – Ordinary Least Squares (Normal Equation) and Gradient Descent methods

**Logistic Regression** – Binary classification with Gradient Descent optimization

**K-Nearest Neighbors (KNN)** – Classification and Regression with multiple distance metrics

## Preprocessing & Transformers

**StandardScaler** – Standardizes features to mean=0, standard deviation=1

**NormalScaler** – Min-max scaling to [0,1]

**LabelEncoder** – Converts categorical labels to integers

**OneHotEncoder** – Converts categorical features into one-hot encoded vectors

**PolynomialFeatures** – Generates polynomial and interaction features up to a given degree

## Base Classes

**BaseModel** – Abstract base class for all models with input validation

**BaseTransformer** – Abstract base class for all transformers with fit, transform, and fit_transform interface

## What’s Inside

**BareMetalML includes**:

All basic regression and classification models to start learning ML from scratch

Preprocessing tools for handling numerical and categorical data

Feature engineering utilities like polynomial feature generation

Modular structure for easy imports and extensibility

## Installation

BareMetalML is available on PyPI. Install it with:

```bash
pip install baremetalml
```
Then import the modules you need:

```python
from baremetalml import LinearRegression, StandardScaler, KNNClassifier
```

## Author 

Askari Abidi

## Contribute & Support

BareMetalML is an open-source educational project.

Feel free to contribute, suggest improvements, or report issues on the repository.

If you find it useful, you can support the project via donations or by sharing it with others.
Every contribution helps make learning ML from scratch easier and more accessible!