Neural Network From Scratch (without any machine learning modules)

Biblioteca para manipulação de modelos de Redes Neurais

This notebook serves as a step-by-step tutorial on building a neural network from scratch using only NumPy and Pandas, focusing on the MNIST dataset.

Just some notebooks I wrote to research some fun stuff in hobby time

Training single-layer perceptrons to get the outputs of OR and AND logic gates.

3 JavaFX based simulations about neural-networks, caesar ciphers and wave behaviours.

Learning C and overoptimising

My first ML sandbox

This is the code for a fully connected neural network. The code is written from scratch using Numpy, without using any ready-made deep learning library. In this, classification is done on the MNIST dataset. It is generalized to include various options for activation functions, loss functions, types of regularization, and output activation types.

Artificial neural network package written in python

Simple Neural Network written from scratch in C++ with a real time interactive and visualization demo.

Simple MLP (Multi-Layer Perceptron) framework with MNIST example

Some exercises codes on basics of machine learning built from scratch with basic libraries like numpy ,math.

Unsupervised Deep Learning-based Pansharpening with Jointly-Enhanced Spectral and Spatial Fidelity

Feed forward neural network implementation from scratch in python using numpy.

Learning by creating a basic machine learning model in Rust w/o external crates for ML functions.

Framework to create, train & test MLPs and RNNs, written from scratch in Java

Tasks for Architecture of Neural Networks Course @ ITMO University

NN Forge: Design neural networks visually with our intuitive GUI, then generate clean Python code to jumpstart your deep learning projects.

Some code as an introduction to neural networks