backward-propagation
There are 50 repositories under backward-propagation topic.
yizt/numpy_neural_network
仅使用numpy从头开始实现神经网络,包括反向传播公式推导过程; numpy构建全连接层、卷积层、池化层、Flatten层；以及图像分类案例及精调网络案例等,持续更新中... ...
navjindervirdee/neural-networks
Implemented Convolutional Neural Network, LSTM Neural Network, and Neural Network From Scratch in Python Language.
hellonlp/deep-learning
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
marcelogcardozo/migracao-sismica
Desenvolvimento de ferramenta para efetuar a Modelagem e a Migração Sísmica de um modelo 2D.
Zahra-Bakhtiari/Building-Deep-Neural-Network-Step-by-Step-Instruction
building a deep neural network with as many layers as you want!
Apoorv070/Deep_learning_Basics
Learning about Perceptron and Multi layered perceptron
brian00715/CNN-From-Scratch
A.K.A. NUS ME5411 Final Project. Implemented a CNN framework without off-the-shelf libraries and its application for character recognition.
FreeFEMExamples/backward_step
backward_step, a FreeFem++ code which solves the backward step benchmark problem for Navier Stokes flow.
samyo00/Neural-Network-from-scratch
Neural Network from scratch using Python and NumPy, featuring forward/backward propagation and basic optimizers. Perfect for learning deep learning fundamentals.
CICIFLY/Deep-Learning-Projects
CNN, ANN, Python, Matlab
Lin-TzuLing/NYCU-DLP-2023
Deep Learning & Labs Course, NYCU, 2023
mattsankner/micrograd
I build the Micrograd autogradient engine, which is a functioning neural network with forward pass, backward propagation, and stochastic gradient descent, all built from scratch. This is derived from the great @karpathy micrograd lecture. Each notebook is complete with Andrei's lecture code and speech, as well as my own code, anecdotes and addition
raffal88/Machine-learning
Python version of Andrew Ng's Machine Learning Course.
Tensor-Array/Tensor-Array
A C++ machine learning framework/library.
xujiachang1024/NumPy-based-Neural-Network
A highly modular design and implementation of fully-connected feedforward neural network structured on NumPy matrices
yashsriram/spnn
A comparison of fully connected network (forward and backward propagation) implementations.
chiapeilin/Neural-Network
The code of forward propagation , cost function , backpropagation and visualize the hidden layer.
iforever-yh/BP_FittingTool
Fit functions using the Backpropagation Algorithm. 一个使用反向传播算法拟合函数的工具。
ml-repos/Deep-Neural-Network
Create a Deep Neural Network from Scratch using Python3.
sef007/Neural-Network-Email-Classifier-Numpy-Only
Neural Network using NumPy, V1: Built from scratch. V2: Optimised with hyperparameter search.
sef007/NN-Numpy-Only-HOG-Feature-Extraction-and-ML-Library-Integration
Digit Recognition Neural Network: Built from scratch using only NumPy. Optimised version includes HOG feature extraction. Third version utilises prebuilt ML libraries.
aadityasikder/Neural-Network-from-Scratch-
This notebook demonstrates a neural network implementation using NumPy, without TensorFlow or PyTorch. Trained on the MNIST dataset, it features an architecture with input layer (784 neurons), two hidden layers (132 and 40 neurons), and an output layer (10 neurons) with sigmoid activation.
Akarshan-Jaiswal/NeuralNetwork
Implementing Neural network from scratch
dhwabqryh/Data-Mining-I
Tugas praktikum Data Mining I
HardikKhatri123/IntroToDeepLearningCourseraSolutions
This repository contains the solutions of Coursera course Intro to Deep Learning Solutions
LiYan-97/CG_SF64
This code uses computational graph and neural network to solve the five-layer traffic demand estimation in Sioux Falls network. It also includes comparison of models and 10 cross-validations.
MohammedSaqibMS/Gradient-Checking
Gradient Checking: Demonstrates 1D and ND gradient checking techniques to verify the accuracy of gradients in neural networks. Inspired by DeepLearning.AI's Deep Learning Specialization.
xahid007/Neural-Netowork
In this repo, I tried to upload basic components of Neural Network. It will eventually help to understand the core ideas of NN.
ErniW/Neural-Network-in-pure-NumPy
A feedforward neural network from scratch without any high level deep learning libraries. Pure mathematics and NumPy.
liviaarumsari/forward-backward-propagation
Tubes IF3270: Machine Learning in Forward and Backward Propagation Implementation
mikeleo03/Artificial-Neural-Network
Implementation of Artificial Neural Network from Scratch using Python and Jupyter Notebook
muhammadshaffay/Text-Clipper
A tool that quickly and accurately segments Urdu sentences and words in your text.
oselin/gradient_ML_LTI
A gentle introduction to custom gradient propagation for ML application in which parameters of LTI systems have to be optimized. This example enables the integration of control theory with machine learning, for the development of Physical-Informed Neural Networks (PINNs)