This resource implements a deep neural network through Numpy, and is equipped with easy-to-understand theoretical derivation, mainly for the in-depth understanding of neural networks. 神经网络模型的理论证明与基于Numpy的实现。

Implementation of key concepts of neuralnetwork via numpy

Deep learning library in python from scratch

A neural network in 13 lines of Python.

A proof of concept of a recursion doing stochastic gradient descent for a simple neural network. Done in Python3 with numpy

This project leverages the high-performance computational power of NumPy alongside the scalable machine learning framework TensorFlow to build a robust end-to-end data pipeline and predictive model.

Python repository for deep learning using Tensorflow and Numpy

Machine learning algorithm implemented from scratch in python

This is an educational project intended to classify handwritten digits from the MNIST database using only native Python and the NumPy library. Pillow (PIL fork) was used to display the handwritten images for demonstration purposes.

Neural Networks and training algorithms in Numpy, for learning purpose.

🤖 Build and train neural networks from scratch using only NumPy, featuring modular layers, object-oriented design, and robust training methods.