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yaricom / TimeSeriesLearning

The project aimed to implement Deep NN / RNN based solution in order to develop flexible methods that are able to adaptively fillin, backfill, and predict time-series using a large number of heterogeneous training datasets.

deep-neural-networks deep-learning time-series recurrent-neural-networks pca-analysis rnn adagrad rmsprop leaky-relu adam-optimizer random-forest-regressor adamax

Updated Aug 16, 2016
Python

prateekbhat91 / Neural-Network

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Python library for neural networks.

neural-network optimizer adagrad rmsprop

Updated Dec 29, 2016
Python

ToKu2015 / NN_DMGA

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neural-network distance deep backpropagation-learning-algorithm backpropagation rmsprop

Updated Aug 15, 2017
MATLAB

sharnam19 / Networks

Star

Library which can be used to build feed forward NN, Convolutional Nets, Linear Regression, and Logistic Regression Models.

neural-network mse batch-normalization convolutional-layers regularization convolutional-neural-networks gradient-descent affine-layer adagrad rmsprop xavier-initializer adam-optimizer softmax-layer relu-layer padding-layer loss-layers

Updated Oct 27, 2017
Python

tansut / ml-framework

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Aibrite Machine Learning Framework

machine-learning deep-learning machine-learning-algorithms test-framework neural-networks machine-learning-library machine-learning-coursera rmsprop adam-optimizer normali

Updated Mar 16, 2018
Python

ElefHead / digit_recognition

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Fully connected neural network for digit classification using MNIST data

tensorflow numpy python3 mnist neural-networks classification mnist-dataset momentum rmsprop he-initializer adam-optimizer mnist-handwriting-recognition amsgrad

Updated Apr 3, 2018
Python

jlabhishek / HowFarIsIt

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Finding distances between two objects in a 2D image

distance keras cnn deeplearning mlp regression-models rmsprop

Updated Apr 7, 2018
Python

srinadhu / convolutional_nn

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Implemented fully-connected DNN of arbitrary depth with Batch Norm and Dropout, three-layer ConvNet with Spatial Batch Norm in NumPy. The update rules used for training are SGD, SGD+Momentum, RMSProp and Adam. Implemented three block ResNet in PyTorch, with 10 epochs of training achieves 73.60% accuracy on test set.

pytorch dropout batch-normalization convolutional-neural-networks rmsprop adam-optimizer cifar-10 pytorch-cnn-classification sgd-optimizer cs231n-assignment fully-connected-deep-neural-network sgd-moment

Updated Jul 6, 2018
Jupyter Notebook

oziomek1 / neural_network_dice

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Notebooks with various models for images recognition based on dices example

neural-network tensorflow keras rmsprop adam-optimizer sequential-models sgd-optimizer

Updated Jul 6, 2018
Jupyter Notebook

alphadl / GD-optimization-algorithms

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gradient descent optimization algorithms

machine-learning rprop adadelta adam adagrad rmsprop optimalisation normal-gd

Updated Aug 21, 2018
Python

barathvaj / Deep-Learning

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Objective here is to explore the concepts of deep learning and implementing it from scratch in a structured way.

deep-neural-networks deep-learning lstm dropout neural-networks deep-learning-algorithms rnn rnn-model adagrad rmsprop adam-optimizer sgd-optimizer

Updated Sep 27, 2018
Jupyter Notebook

mmahesh / variants-of-rmsprop-and-adagrad

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SC-Adagrad, SC-RMSProp and RMSProp algorithms for training deep networks proposed in

python deep-neural-networks deep-learning optimization keras online-learning adagrad rmsprop stochastic-gradient-descent

Updated Oct 5, 2018
Python

somefunAgba / deeplearningWithMatlabinPy

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Investigating the Behaviour of Deep Neural Networks for Classification

deep-neural-networks deep-learning optimization images dropout batch-normalization numbers classification gradient-descent backpropagation-learning-algorithm rmsprop softmax cross-entropy adamax black-and-white relu

Updated Oct 7, 2018
Python

Mypathissional / GradientDescentAlgorithms

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The implementation of famous Gradient Descent Algorithms along with nice visualizations in Matlab

animation matlab rmsprop ackley adam-optimizer nesterov-momentum gradient-descent-algos

Updated Oct 22, 2018
MATLAB

falaktheoptimist / gradient_descent_optimizers

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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

Updated Dec 20, 2018
Jupyter Notebook

DunittMonagas / Improving-Deep-Neural-Networks-Hyperparameter-tuning-Regularization-and-Optimization

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Curso Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization. Segundo curso del programa especializado Deep Learning. Este repositorio contiene todos los ejercicios resueltos. https://www.coursera.org/learn/neural-networks-deep-learning

tensorflow dropout batch-normalization momentum gradient-descent hyperparameter-tuning l2-regularization rmsprop stochastic-gradient-descent adam-optimizer mini-batch-gradient-descent gradient-check

Updated Jan 11, 2019
Jupyter Notebook

SSQ / Coursera-Ng-Improving-Deep-Neural-Networks-Hyperparameter-tuning-Regularization-and-Optimization

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Short description for quick search

tensorflow dropout batch-normalization momentum softmax-regression l2-regularization rmsprop adam-optimizer mini-batch-gradient-descent bias-correction initialization gradient-check exponentially-weighted-averages learning-rate-decay

Updated Jan 31, 2019
Python

Nasdin / ReinforcementLearning-AtariGame

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Pytorch LSTM RNN for reinforcement learning to play Atari games from OpenAI Universe. We also use Google Deep Mind's Asynchronous Advantage Actor-Critic (A3C) Algorithm. This is much superior and efficient than DQN and obsoletes it. Can play on many games

python reinforcement-learning deep-reinforcement-learning openai-gym pytorch lstm reinforcement-learning-algorithms a3c universe adam rmsprop actor-critic asynchronous-advantage-actor-critic reinforcement-agents a3c-lstm

Updated Feb 27, 2019
Jupyter Notebook

harshraj11584 / Paper-Implementation-Overview-Gradient-Descent-Optimization-Sebastian-Ruder

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[Python] [arXiv/cs] Paper "An Overview of Gradient Descent Optimization Algorithms" by Sebastian Ruder

Updated Mar 23, 2019
Python

zahramajd / neural-network-from-scratch

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building a neural network classifier from scratch using Numpy

deep-learning neural-network numpy adagrad rmsprop adam-optimizer cifar10-classification

Updated Apr 6, 2019
Python

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Here are 101 public repositories matching this topic...

yaricom / TimeSeriesLearning

prateekbhat91 / Neural-Network

ToKu2015 / NN_DMGA

sharnam19 / Networks

tansut / ml-framework

ElefHead / digit_recognition

jlabhishek / HowFarIsIt

srinadhu / convolutional_nn

oziomek1 / neural_network_dice

alphadl / GD-optimization-algorithms

barathvaj / Deep-Learning

mmahesh / variants-of-rmsprop-and-adagrad

somefunAgba / deeplearningWithMatlabinPy

Mypathissional / GradientDescentAlgorithms

falaktheoptimist / gradient_descent_optimizers

DunittMonagas / Improving-Deep-Neural-Networks-Hyperparameter-tuning-Regularization-and-Optimization

SSQ / Coursera-Ng-Improving-Deep-Neural-Networks-Hyperparameter-tuning-Regularization-and-Optimization

Nasdin / ReinforcementLearning-AtariGame

harshraj11584 / Paper-Implementation-Overview-Gradient-Descent-Optimization-Sebastian-Ruder

zahramajd / neural-network-from-scratch

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