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GitHub topics: momentum-optimization-algorithm

nabeelshan78/deep-nn-from-scratch

A fully vectorized Deep Neural Network (DNN) implementation built from scratch using only NumPy - no deep learning frameworks involved. Covers forward/backward propagation, activation functions, modular architecture, and training with different optimizers - a hands-on deep dive into the fundamentals of deep learning.

Language: Jupyter Notebook - Size: 8.42 MB - Last synced at: 10 days ago - Pushed at: 10 days ago - Stars: 0 - Forks: 0

kinit-sk/overshoot

Overshoot: Taking advantage of future gradients in momentum-based stochastic optimization

Language: Python - Size: 488 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 2 - Forks: 0

mkgeiger/neural-network

Simple neural-network supporting most importent features like Convolutional-/Fully Connected network completely written in Ansi C

Language: C - Size: 65.4 KB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 1 - Forks: 0

SaiCodePro/DFSM-Det

Intelligent Detection for RIS-Assisted MIMO Systems: A First-and-Second Momentum Approach

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aahouzi/Simple_Document_Classification_From_Scratch

Simple Document Classification using Multi Class Logistic Regression & SVM Soft Margin from scratch

Language: Jupyter Notebook - Size: 80.1 KB - Last synced at: about 1 month ago - Pushed at: almost 3 years ago - Stars: 1 - Forks: 0

AsmaaEssamSultan/Optimization-Techniques-from-scratch

Language: Jupyter Notebook - Size: 1.14 MB - Last synced at: 8 months ago - Pushed at: about 3 years ago - Stars: 1 - Forks: 0

aysekonus/ml_optimization_algorithms

Comparsion of Machine Learning optimization algorithms with MNIST dataset

Language: Jupyter Notebook - Size: 181 KB - Last synced at: over 1 year ago - Pushed at: about 3 years ago - Stars: 0 - Forks: 0

Efesasa0/mlp-backprop-two-moons

EE456 2022 mini project implementation of two-moons problem using multi-layer-perceptron with back-propagation with analyzing performance of initializing methods and momentum rule

Language: MATLAB - Size: 5.31 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

ravikumarchopra/DL-Assignment-1

This repository contains a python implementation of Feed Forward Neural Network with Backpropagation, along with the example scripts for training the network to classify images from mnist and fashion_mnist datasets from keras.

Language: Jupyter Notebook - Size: 36.1 KB - Last synced at: almost 2 years ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0

skolai/nag-gs

NAG-GS: Nesterov Accelerated Gradients with Gauss-Siedel splitting

Language: Python - Size: 459 KB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 8 - Forks: 1

aliejabbari/Optimizations-ADAM-Momentum-SGD

Python code for Gradient Descent, Momentum, and Adam optimization methods. Train neural networks efficiently.

Language: Jupyter Notebook - Size: 189 KB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

AlbertoMarinelli/QRI-ELM-and-ELM-with-Standard-Momentum

In this project it is used a Machine Learning model based on a method called Extreme Learning, with the employment of L2-regularization. In particular, a comparison was carried out between: (A1) which is a variant of incremental extreme learning machine that is QRIELM and (A2) which is a standard momentum descent approach, applied to the ELM.

Language: MATLAB - Size: 966 KB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

Heba-Atef99/ML_optimization_algorithms

This is an implementation of different optimization algorithms such as: - Gradient Descent (stochastic - mini-batch - batch) - Momentum - NAG - Adagrad - RMS-prop - BFGS - Adam Also, most of them are implemented in vectorized form for multi-variate problems

Language: Jupyter Notebook - Size: 7.34 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

mohadeseh-ghafoori/Optimization-Methods

Language: Jupyter Notebook - Size: 391 KB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0

Arko98/Gradient-Descent-Algorithms

A collection of various gradient descent algorithms implemented in Python from scratch

Language: Python - Size: 1.02 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 19 - Forks: 12

zeke-xie/Positive-Negative-Momentum

The official PyTorch Implementations of Positive-Negative Momentum Optimizers (ICML 2021).

Language: Python - Size: 180 KB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 25 - Forks: 6

hager51/Numerical-Optimization

Numerical Optimization for Machine Learning & Data Science

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Shresth-Mehta/Neural_Networks_API

Machine Learning, Deep Learning Implementations

Language: Jupyter Notebook - Size: 149 KB - Last synced at: over 2 years ago - Pushed at: almost 4 years ago - Stars: 0 - Forks: 0

stxupengyu/Matrix-Factorization-for-Recommendation

Using Matrix Factorization/Probabilistic Matrix Factorization to solve Recommendation。矩阵分解进行推荐系统算法。

Language: R - Size: 10 MB - Last synced at: over 2 years ago - Pushed at: over 5 years ago - Stars: 2 - Forks: 0

Related Keywords
momentum-optimization-algorithm 19 adam-optimizer 8 gradient-descent 7 rmsprop 6 machine-learning 6 deep-learning 6 adagrad 5 python 4 stochastic-gradient-descent 3 optimization 3 matplotlib 2 sgd-optimizer 2 nag-optimizer 2 ai 2 mini-batch 2 machine-learning-algorithms 2 mini-batch-gradient-descent 2 neural-networks 2 pytorch 2 adam 2 optimizer 2 rmsprop-optimizer 2 neural-network 2 nesterov-accelerated-sgd 2 numpy 2 multivariate 1 pmf 1 bfgs-algorithm 1 batch 1 qri-elm 1 qr-factorization 1 incremental-elm 1 extreme-learning-machine 1 nestrov 1 matrix-factorization 1 koren 1 k-means-clustering 1 density-based-clustering 1 pandas 1 batch-gradient-descent 1 stochastic-optimization 1 nesterov-momentum 1 nesterov 1 ml 1 gradient-descent-algorithm 1 deep-learning-algorithms 1 optimization-methods 1 learning-rate-scheduling 1 learning-rate-decay 1 decision-boundary 1 stochastic 1 nag 1 nadam 1 mimo 1 tanh 1 softsign 1 softmax-layer 1 sigmoid 1 relu-layer 1 mean-square-error 1 leaky-relu 1 image-classification 1 glorot-uniform 1 fully-connected-network 1 convolutional-neural-network 1 categorical-cross-entropy 1 vectorization 1 backpropagation 1 deep-learning-from-scratch 1 feedforward-neural-network 1 multi-layer-perceptron 1 back-propagation 1 optimization-algorithms 1 mnist-dataset 1 mnist-classification 1 stocahstic 1 multivariate-regression 1 linear-regression 1 svm-classifier 1 natural-language-processing 1 logistic-regression 1 symbol-detection 1 ris 1 reconfigurable-intelligent-surface 1 multiple-input-multiple-output 1