felipeadeildo/neural-network

Neural Network written from Scratch without libraries like tensorflow (documented)

14
/ 100
Experimental

This project offers a clear, step-by-step guide to the foundational concepts of neural networks. It explains how these models learn from data, process inputs like images or numerical features, and produce predictions or classifications. It's designed for anyone seeking a deep, mathematical understanding of how neural networks are built and trained from scratch.

No commits in the last 6 months.

Use this if you are a student, educator, or researcher who wants to learn the core algorithms and mathematics behind neural networks, without relying on pre-built machine learning frameworks.

Not ideal if you need to quickly build or deploy a practical machine learning application, as this project focuses on theoretical understanding rather than production-ready tools.

artificial-intelligence-education machine-learning-theory algorithm-explanation mathematical-modeling deep-learning-fundamentals
No License Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 4 / 25
Maturity 8 / 25
Community 0 / 25

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Language

Python

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Last pushed

May 14, 2025

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