forward-propagation
There are 75 repositories under forward-propagation topic.
olivia-ai/the-math-behind-a-neural-network
Mathematics paper recapitulating the calculus behind a neural network and its back propagation
navjindervirdee/neural-networks
Implemented Convolutional Neural Network, LSTM Neural Network, and Neural Network From Scratch in Python Language.
Akramz/grokking-deep-learning-notebooks
Notes & Code to go over "Grokking Deep Learning" Book by Andrew Trask
dr-mushtaq/Deep-Learning
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)
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
srilakshmi-thota/IRIS-DATASET-ANALYSIS-USING-NEURAL-NETWORK
Neural Network with functions for forward propagation, error calculation and back propagation is built from scratch and is used to analyse the IRIS dataset.
matsjfunke/feedforward-neural-network-from-scratch
Fully Connected Neural Network (FCNN) from scratch in python & Notes to aid understanding the workings of neural networks
bhavaniprasad73/Artificial-Neural-Network
Artificial Neural Network - Wisconsin Breast Cancer Detection
LeeSinLiang/Neural-Network-Manim
Code for my youtube video: Neural Network Crash Course, Ep 1
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
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
raffal88/Machine-learning
Python version of Andrew Ng's Machine Learning Course.
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.
Access-Denied-001/Neural-Net
Neural Network made by using numpy
alessiopittiglio/image-processing-transmission
Exercises done during the Image Processing and Transmission course
ashish230897/Deep-Neural-Networks-From-Scratch
Designing Your Own Deep Neural Network
chiapeilin/Neural-Network
The code of forward propagation , cost function , backpropagation and visualize the hidden layer.
ejdecena/Redes-Neuronales
Este repositorio sirve de apoyo en la asignatura de Redes Neuronales.
imkalyan/Neuralnetworks
Some algorithms which uses neural networks to solve i.e., forwardpropagation , etc.,
krtab/fwd_ad
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.
lmbarr/cnn_mnist
CNN MATLAB implementation (including training and forward propagation) to clasifify the MNIST handwritten numbers.
NeckersBOX/n3lib
Neural Network library customizable written in C. Threads implementations in both forward and backward propagation.
OMEGAMAX10/Machine-Learning-Programming-Assigments-Coursera-Andrew-Ng
These are the solutions to the programming assigments from Andrew Ng's "Machine Learning" course from Coursera
PasaOpasen/cost2fitness
PyPI package for 1) conversion cost values (less is better) to fitness values (more is better) and vice versa, 2) using fast neural networks for forward propagation
pradeepdev-1995/Gradient-descent
Gradient descent is a first-order iterative optimization algorithm for finding a local minimum of a differentiable function. To find a local minimum of a function using gradient descent, we take steps proportional to the negative of the gradient (or approximate gradient) of the function at the current point. But if we instead take steps proportional to the positive of the gradient, we approach a local maximum of that function; the procedure is then known as gradient ascent.
rainaa0277/Fashion-MNIST-Classifier-using-ANN
Fashion training set consist of 70,000 images divided into 60,000 training and 10,000 testing samples. Dataset samples consists of 28x28 grayscale image associated with a label from 10 calsses.
sef007/Neural-Network-Email-Classifier-Numpy-Only
Neural Network using NumPy, V1: Built from scratch. V2: Optimised with hyperparameter search.
DenisEfremov71/ANN_ForwardPropagation
Jupyter Notebook that builds a Neural Network from scratch
MohammedSaqibMS/Building-your-Deep-Neural-Network
This repository guides you in building deep neural networks from scratch using Python and NumPy, covering key concepts like forward propagation and cost functions for binary classification.
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.
MohammedSaqibMS/Introduction-to-TensorFlow
This repository implements a basic neural network in TensorFlow, covering forward propagation, cost computation, and model training. It is inspired by the Deep Learning Specialization from DeepLearning.AI and provides a hands-on approach to deep learning. 🌟
liviaarumsari/forward-backward-propagation
Tubes IF3270: Machine Learning in Forward and Backward Propagation Implementation