Neural Tool Kit (NTK)

Neural Tool Kit (NTK) is a NumPy-based machine learning framework built from scratch in Python. The project aims to provide a hands-on exploration of the core systems behind modern deep learning frameworks, including tensors, automatic differentiation, neural network layers, optimization, and training workflows.

I designed NTK as a learning-focused project to explore the fundamental systems behind modern deep learning frameworks. While it serves as a personal educational project, it may also be useful to students, hobbyists, and anyone interested in understanding how machine learning frameworks work internally.

Motivation

I built NTK to develop a deeper understanding of the systems that power modern deep learning frameworks. By implementing these components from scratch, I can explore how they work internally rather than treating them as black boxes.

Installation

pip install ntk-ml

Quick Start

import neuraltoolkit as ntk

x = ntk.Tensor([[1, 2], [3, 4]])

print(x)

model = ntk.Sequential(
    ntk.Dense(2, 4),
    ntk.Relu(),
    ntk.Dense(4, 1)
)