Mathematics paper recapitulating the calculus behind a neural network and its back propagation

Implemented Convolutional Neural Network, LSTM Neural Network, and Neural Network From Scratch in Python Language.

Notes & Code to go over "Grokking Deep Learning" Book by Andrew Trask

This repository is a related to all about Deep Learning - an A-Z guide to the world of Data Science. This supplement contains the implementation of algorithms, statistical methods and techniques (in Python)

搭建、深度学习、前向传播、反向传播、梯度下降和模型参数更新、classification、forward-propagation、backward-propagation、gradient descent、python、text classification

Neural Network with functions for forward propagation, error calculation and back propagation is built from scratch and is used to analyse the IRIS dataset.

Fully Connected Neural Network (FCNN) from scratch in python & Notes to aid understanding the workings of neural networks

Code for my youtube video: Neural Network Crash Course, Ep 1

building a deep neural network with as many layers as you want!

Artificial Neural Network - Wisconsin Breast Cancer Detection

Learning about Perceptron and Multi layered perceptron

Neural Network from scratch using Python and NumPy, featuring forward/backward propagation and basic optimizers. Perfect for learning deep learning fundamentals.

Python version of Andrew Ng's Machine Learning Course.

A highly modular design and implementation of fully-connected feedforward neural network structured on NumPy matrices

CNN, ANN, Python, Matlab

A comparison of fully connected network (forward and backward propagation) implementations.

Este repositorio sirve de apoyo en la asignatura de Redes Neuronales.

Exercises done during the Image Processing and Transmission course

Fwd:AD is a Rust library (crate) to perform forward auto-differentiation, with a focus on empowering its user to manage memory location and minimize copying. This repo is a mirror of https://gitlab.inria.fr/InBio/Public/fwd_ad.