Educational deep learning library in plain Numpy.
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Jun 21, 2022 - Python
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nesterov-accelerated-sgd
Here are 20 public repositories matching this topic...
A collection of various gradient descent algorithms implemented in Python from scratch
machine-learning ai deep-learning machine-learning-algorithms ml deep-learning-algorithms gradient-descent adagrad rmsprop gradient-descent-algorithm adam-optimizer nesterov-accelerated-sgd nesterov-momentum nesterov momentum-optimization-algorithm
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Feb 28, 2023 - Python
[Python] [arXiv/cs] Paper "An Overview of Gradient Descent Optimization Algorithms" by Sebastian Ruder
adadelta momentum gradient-descent optimization-methods optimization-algorithms adam adagrad rmsprop gradient-descent-algorithm stochastic-optimizers stochastic-gradient-descent gradient-boosting adam-optimizer adamax stochastic-optimization batch-gradient-descent nesterov-accelerated-sgd amsgrad nesterov-momentum nadam
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Mar 23, 2019 - Python
From linear regression towards neural networks...
data-science machine-learning neural-network linear-regression machine-learning-algorithms data-analysis logistic-regression gradient-descent backpropagation adagrad rmsprop generalized-linear-models multilayer-perceptron-network adam-optimizer nesterov-accelerated-sgd nesterov-momentum nadam
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Sep 21, 2024 - C++
NAG-GS: Nesterov Accelerated Gradients with Gauss-Siedel splitting
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Dec 3, 2022 - Python
Hands on implementation of gradient descent based optimizers in raw python
python optimizer python3 adadelta sgd gradient-descent adagrad rmsprop adam-optimizer nesterov-accelerated-sgd
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Dec 20, 2018 - Jupyter Notebook
Neural Networks and optimizers from scratch in NumPy, featuring newer optimizers such as DemonAdam or QHAdam.
numpy adadelta neural-networks mnist-dataset backpropagation rmsprop nesterov-accelerated-sgd neural-networks-from-scratch optimizers qhadam demon-adam
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Feb 10, 2021 - Jupyter Notebook
ASCPD: an accelerated algorithm for CPD
matlab openmp matrix-factorization decomposition tensors optimization-algorithms eigen-library nesterov-accelerated-sgd stochastic-algorithms
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Oct 3, 2021 - C++
ISANet is a Neural Network Library.
machine-learning deep-neural-networks deep-learning neural-network sgd neural-networks machine-learning-library machinelearning deeplearning momentum gradient-descent ball neural neuralnetwork nesterov-accelerated-sgd heavy-ball
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Mar 14, 2023 - Python
Primal-Dual algorithm for smooth regularization of non-smooth optimization functions
gradient-descent adam-optimizer gaussian-kernel nesterov-accelerated-sgd tikhonov-regularization optimization-techniques primal-dual-algorithm chambolle-pock
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Dec 9, 2023 - MATLAB
Implementation of SVD without using package.
recommender-system regularization momentum stochastic-gradient-descent singular-value-decomposition nesterov-accelerated-sgd
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Nov 28, 2017 - Python
"Simulations for the paper 'A Review Article On Gradient Descent Optimization Algorithms' by Sebastian Roeder"
python batch adadelta artificial-neural-networks gradient gradient-descent adam adagrad rmsprop gradient-descent-algorithm artificial-intelligence-algorithms nesterov-accelerated-sgd numpy-library sebastian amsgrad damax nadam sympy-library scipy-library momentum-gradient-descent
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Jun 19, 2024 - Jupyter Notebook
Package used for mathematical optimization.
java optimization optimization-algorithms adagrad rmsprop stochastic-gradient-descent adam-optimizer nesterov-accelerated-sgd
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Sep 13, 2019 - Java
🧠Implementation of a Neural Network from scratch in Python for the Machine Learning Course.
machine-learning neural-network regression classification backpropagation bias-variance multilayer-perceptron-network mlp-regressor nesterov-accelerated-sgd mlp-classifier sgd-optimizer nesterov-momentum
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Oct 15, 2021 - Python
SVM algorithms implementation from scratch for AI539 class project
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Dec 13, 2022 - Python
Implemented optimization algorithms, including Momentum, AdaGrad, RMSProp, and Adam, from scratch using only NumPy in Python. Implemented the Broyden-Fletcher-Goldfarb-Shanno (BFGS) optimizer and conducted a comparative analysis of its results with those obtained using Adam.
optimization momentum optimization-algorithms adagrad rmsprop adam-optimizer nesterov-accelerated-sgd bfgs-algorithm
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May 18, 2023 - Jupyter Notebook
Digit recognition neural network using the MNIST dataset. Features include a full gui, convolution, pooling, momentum, nesterov momentum, RMSProp, batch normalization, and deep networks.
neural-network mnist neural-networks mnist-dataset image-classification image-recognition convolution convolutional-neural-networks gradient-descent neural-nets rmsprop stochastic-gradient-descent neuralnetworks pooling batchnorm nesterov-accelerated-sgd mnist-handwriting-recognition transposedconvolution nesterov-momentum
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Jun 8, 2020 - C#
Assignment submission for the course Fundamentals of Deep Learning (CS6910) in the Spring 2022 Semester, under Prof. Mitesh Khapra
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Jul 6, 2022 - Jupyter Notebook
Repository with the submissions for the 'Fundamentals of Optimization' course, where techniques such as gradient descent and its variants are implemented. These include gradient descent with a fixed step size (alpha), Nesterov GD with a fixed step, GD with a decreasing step size, GD with diagonal scaling and fixed step size.
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Dec 19, 2023 - Jupyter Notebook
This repository contains various tools of machine learning like the GRADIENT DESCENT and others, implemented from scratch using packages like numPy, matplotlib, pandas
python machine-learning deep-learning neural-network numpy gradient-descent adam-optimizer nesterov-accelerated-sgd polyak-momentum rosenbrock-function-optimization
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Oct 7, 2022 - Jupyter Notebook
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