dropout | Topic | Ecosyste.ms: Repos

Topic: "dropout"

MorvanZhou/PyTorch-Tutorial

Build your neural network easy and fast, 莫烦Python中文教学

Language: Jupyter Notebook - Size: 14.7 MB - Last synced at: 11 days ago - Pushed at: about 2 years ago - Stars: 8,303 - Forks: 3,109

MorvanZhou/Tensorflow-Tutorial

Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学

Language: Python - Size: 37.1 MB - Last synced at: 3 days ago - Pushed at: over 4 years ago - Stars: 4,346 - Forks: 1,866

Pizzacus/satania.moe

Satania IS the BEST waifu, no really, she is, if you don't believe me, this website will convince you

Language: HTML - Size: 47.9 MB - Last synced at: 2 days ago - Pushed at: over 2 years ago - Stars: 614 - Forks: 57

miguelvr/dropblock

Implementation of DropBlock: A regularization method for convolutional networks in PyTorch.

Language: Python - Size: 48.8 KB - Last synced at: 8 days ago - Pushed at: almost 5 years ago - Stars: 596 - Forks: 95

parasdahal/deepnet

Educational deep learning library in plain Numpy.

Language: Python - Size: 40 KB - Last synced at: 6 months ago - Pushed at: almost 3 years ago - Stars: 322 - Forks: 83

JonathanRaiman/theano_lstm

:microscope: Nano size Theano LSTM module

Language: Python - Size: 91.8 KB - Last synced at: 7 days ago - Pushed at: over 8 years ago - Stars: 303 - Forks: 112

Jackpopc/aiLearnNotes

Artificial Intelligence Learning Notes.

Language: Python - Size: 638 KB - Last synced at: 11 days ago - Pushed at: about 2 years ago - Stars: 273 - Forks: 60

Cohere-Labs-Community/Targeted-Dropout

Complementary code for the Targeted Dropout paper

Language: Python - Size: 62.5 KB - Last synced at: about 1 month ago - Pushed at: over 5 years ago - Stars: 255 - Forks: 46

hwalsuklee/tensorflow-mnist-cnn

MNIST classification using Convolutional NeuralNetwork. Various techniques such as data augmentation, dropout, batchnormalization, etc are implemented.

Language: Python - Size: 168 MB - Last synced at: 19 days ago - Pushed at: almost 7 years ago - Stars: 202 - Forks: 96

ivannz/cplxmodule

Complex-valued neural networks for pytorch and Variational Dropout for real and complex layers.

Language: Python - Size: 473 KB - Last synced at: 6 days ago - Pushed at: almost 3 years ago - Stars: 144 - Forks: 28

noahfl/densenet-sdr 📦

repo that holds code for improving on dropout using Stochastic Delta Rule

Language: Python - Size: 104 KB - Last synced at: over 1 year ago - Pushed at: over 6 years ago - Stars: 143 - Forks: 15

seba-1511/lstms.pth

PyTorch implementations of LSTM Variants (Dropout + Layer Norm)

Language: Python - Size: 40 KB - Last synced at: about 2 months ago - Pushed at: about 4 years ago - Stars: 136 - Forks: 24

AnicetNgrt/jiro-nn

A Deep Learning and preprocessing framework in Rust with support for CPU and GPU.

Language: Rust - Size: 17.5 MB - Last synced at: 11 days ago - Pushed at: over 1 year ago - Stars: 131 - Forks: 3

lonePatient/daguan_2019_rank9

datagrand 2019 information extraction competition rank9

Language: Python - Size: 4.2 MB - Last synced at: about 2 months ago - Pushed at: over 5 years ago - Stars: 130 - Forks: 43

VITA-Group/Deep_GCN_Benchmarking

[TPAMI 2022] "Bag of Tricks for Training Deeper Graph Neural Networks A Comprehensive Benchmark Study" by Tianlong Chen*, Kaixiong Zhou*, Keyu Duan, Wenqing Zheng, Peihao Wang, Xia Hu, Zhangyang Wang

Language: Python - Size: 805 KB - Last synced at: about 1 month ago - Pushed at: over 3 years ago - Stars: 125 - Forks: 21

Single (i) Cell R package (iCellR) is an interactive R package to work with high-throughput single cell sequencing technologies (i.e scRNA-seq, scVDJ-seq, scATAC-seq, CITE-Seq and Spatial Transcriptomics (ST)).

Language: R - Size: 68.2 MB - Last synced at: 21 days ago - Pushed at: 11 months ago - Stars: 122 - Forks: 19

snrazavi/Machine-Learning-in-Python-Workshop

My workshop on machine learning using python language to implement different algorithms

Language: Jupyter Notebook - Size: 23 MB - Last synced at: over 1 year ago - Pushed at: over 5 years ago - Stars: 111 - Forks: 63

j-min/Dropouts

PyTorch Implementations of Dropout Variants

Language: Jupyter Notebook - Size: 3.91 KB - Last synced at: 16 days ago - Pushed at: over 7 years ago - Stars: 87 - Forks: 18

Randl/DropBlock-pytorch

Implementation of DropBlock in Pytorch

Language: Python - Size: 4.88 KB - Last synced at: over 2 years ago - Pushed at: over 6 years ago - Stars: 78 - Forks: 18

thtrieu/essence

AutoDiff DAG constructor, built on numpy and Cython. A Neural Turing Machine and DeepQ agent run on it. Clean code for educational purpose.

Language: Python - Size: 19.4 MB - Last synced at: 23 days ago - Pushed at: over 5 years ago - Stars: 77 - Forks: 18

anassinator/bnn

Bayesian Neural Network in PyTorch

Language: Python - Size: 415 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 76 - Forks: 25

KlugerLab/ALRA

Imputation method for scRNA-seq based on low-rank approximation

Language: R - Size: 7.72 MB - Last synced at: over 1 year ago - Pushed at: about 2 years ago - Stars: 63 - Forks: 18

emilwallner/Deep-Learning-101

The tools and syntax you need to code neural networks from day one.

Language: Jupyter Notebook - Size: 11.7 KB - Last synced at: about 1 month ago - Pushed at: over 7 years ago - Stars: 60 - Forks: 15

ahmedfgad/CIFAR10CNNFlask

Building a HTTP-accessed convolutional neural network model using TensorFlow NN (tf.nn), CIFAR10 dataset, Python and Flask.

Language: Python - Size: 45.9 KB - Last synced at: about 1 month ago - Pushed at: about 2 years ago - Stars: 59 - Forks: 35

georgezoto/TensorFlow-in-Practice

TensorFlow in Practice Specialization. Join our Deep Learning Adventures community 🎉 and become an expert in Deep Learning, TensorFlow, Computer Vision, Convolutional Neural Networks, Kaggle Challenges, Data Augmentation and Dropouts Transfer Learning, Multiclass Classifications and Overfitting and Natural Language Processing NLP as well as Time Series Forecasting 😀 All while having fun learning and participating in our Deep Learning Trivia games 🎉 http://bit.ly/deep-learning-tf

Language: Jupyter Notebook - Size: 124 MB - Last synced at: over 1 year ago - Pushed at: almost 5 years ago - Stars: 59 - Forks: 24

aditya9211/SVHN-CNN

Google Street View House Number(SVHN) Dataset, and classifying them through CNN

Language: Jupyter Notebook - Size: 1.02 MB - Last synced at: over 2 years ago - Pushed at: about 7 years ago - Stars: 58 - Forks: 34

VITA-Group/Random-MoE-as-Dropout

[ICLR 2023] "Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers" by Tianlong Chen*, Zhenyu Zhang*, Ajay Jaiswal, Shiwei Liu, Zhangyang Wang

Language: Python - Size: 686 KB - Last synced at: about 1 month ago - Pushed at: over 2 years ago - Stars: 50 - Forks: 2

xuwd11/Dropout_Tutorial_in_PyTorch

Dropout as Regularization and Bayesian Approximation

Language: Jupyter Notebook - Size: 327 MB - Last synced at: almost 2 years ago - Pushed at: over 6 years ago - Stars: 50 - Forks: 26

hwalsuklee/numpy-neuralnet-exercise

Implementation of key concepts of neuralnetwork via numpy

Language: Python - Size: 26.4 MB - Last synced at: about 1 month ago - Pushed at: over 7 years ago - Stars: 48 - Forks: 13

kefirski/variational_dropout

Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch

Language: Python - Size: 21.5 KB - Last synced at: about 2 years ago - Pushed at: over 7 years ago - Stars: 46 - Forks: 4

mosswg/dropout-dl

A tool for downloading dropout.tv episodes

Language: C++ - Size: 251 KB - Last synced at: 9 days ago - Pushed at: 9 days ago - Stars: 44 - Forks: 7

zmyzheng/Neural-Networks-and-Deep-Learning

Deep learning projects including applications (face recognition, neural style transfer, autonomous driving, sign language reading, music generation, translation, speech recognition and NLP) and theories (CNNs, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, hyperparameter tuning, regularization, optimization, Residual Networks). Deep Learning Specialization by Andrew Ng, deeplearning.ai

Language: Jupyter Notebook - Size: 662 MB - Last synced at: 25 days ago - Pushed at: over 6 years ago - Stars: 40 - Forks: 13

srinadhu/CS231n

My solutions for Assignments of CS231n: Convolutional Neural Networks for Visual Recognition

Language: Jupyter Notebook - Size: 11.3 MB - Last synced at: 10 months ago - Pushed at: over 6 years ago - Stars: 40 - Forks: 23

da-molchanov/variance-networks

Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019

Language: Python - Size: 37.1 KB - Last synced at: over 2 years ago - Pushed at: over 5 years ago - Stars: 39 - Forks: 3

RabadanLab/randomly

A Library for Denoising Single-Cell Data with Random Matrix Theory

Language: Jupyter Notebook - Size: 4.52 MB - Last synced at: 5 days ago - Pushed at: almost 2 years ago - Stars: 37 - Forks: 10

sungyubkim/MCDO

A pytorch implementation of MCDO(Monte-Carlo Dropout methods)

Language: Jupyter Notebook - Size: 233 KB - Last synced at: about 2 years ago - Pushed at: over 6 years ago - Stars: 37 - Forks: 7

fahadm/Bayesian-Active-Learning-Pytorch 📦

Implementation of Bayesian NNs in Pytorch (https://arxiv.org/pdf/1703.02910.pdf) (With some help from https://github.com/Riashat/Deep-Bayesian-Active-Learning/))

Language: Jupyter Notebook - Size: 5.2 MB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 31 - Forks: 4

CyberZHG/keras-drop-block 📦

DropBlock implemented in Keras

Language: Python - Size: 13.7 KB - Last synced at: 11 days ago - Pushed at: over 3 years ago - Stars: 26 - Forks: 15

cvqluu/dropclass_speaker

DropClass and DropAdapt - repository for the paper accepted to Speaker Odyssey 2020

Language: Python - Size: 178 KB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 21 - Forks: 13

pmorerio/curriculum-dropout

Code for the paper "Curriculum Dropout", ICCV 2017

Language: Python - Size: 41 KB - Last synced at: about 2 years ago - Pushed at: about 7 years ago - Stars: 21 - Forks: 7

DelTA-Lab-IITK/U-CAM

Visual Explanation using Uncertainty based Class Activation Maps

Language: Python - Size: 4.21 MB - Last synced at: almost 2 years ago - Pushed at: over 5 years ago - Stars: 19 - Forks: 3

mayur7garg/PlantLeafDiseaseDetection

Deep learning using CNN in tensorflow on Kaggle image dataset containing 87,900 different healthy and unhealthy crop leaves spanning 38 unique classes.

Language: Jupyter Notebook - Size: 29.9 MB - Last synced at: about 2 years ago - Pushed at: about 4 years ago - Stars: 18 - Forks: 3

PRIS-CV/AdvancedDropout

Advanced Dropout: A Model-free Methodology for Bayesian Dropout Optimization (IEEE TPAMI 2021)

Language: Python - Size: 17.6 KB - Last synced at: about 1 month ago - Pushed at: almost 4 years ago - Stars: 17 - Forks: 1

rakibhhridoy/AnomalyDetectionInTimeSeriesData-Keras

Statistics, signal processing, finance, econometrics, manufacturing, networking[disambiguation needed] and data mining, anomaly detection (also outlier detection) is the identification of rare items, events or observations which raise suspicions by differing significantly from the majority of the data. Typically the anomalous items will translate to some kind of problem such as bank fraud, a structural defect, medical problems or errors in a text. Anomalies are also referred to as outliers, novelties, noise, deviations and exceptions.

Language: Jupyter Notebook - Size: 7.6 MB - Last synced at: about 2 months ago - Pushed at: almost 5 years ago - Stars: 17 - Forks: 2

sharmaroshan/Weed-Detection

This Problem is based on a Image Data set consisting of different types of weeds, to detect them in crops and fields. I have used Deep Learning Model called CNN(Convolutional Neural Networks) with Dropout, Batch Normalization, ReduceLearning rate on plateau, Early stoppig rounds, and Transposd Convolutional Neural Networks.

Language: Jupyter Notebook - Size: 25.4 KB - Last synced at: over 1 year ago - Pushed at: almost 6 years ago - Stars: 17 - Forks: 9

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

Short description for quick search

Language: Python - Size: 7.87 MB - Last synced at: over 1 year ago - Pushed at: over 6 years ago - Stars: 17 - Forks: 18

tayebiarasteh/DeepLearning_from_scratch

A Deep Learning framework for CNNs and LSTMs from scratch, using NumPy.

Language: Python - Size: 11.8 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 16 - Forks: 2

AdalbertoCq/NeuralNetwork

Neural Network implementation in Numpy and Keras. Batch Normalization, Dropout, L2 Regularization and Optimizers

Language: Python - Size: 8.01 MB - Last synced at: about 1 year ago - Pushed at: about 6 years ago - Stars: 16 - Forks: 6

cjratcliff/variational-dropout

TensorFlow implementation of the method from Variational Dropout Sparsifies Deep Neural Networks, Molchanov et al. (2017)

Language: Python - Size: 43 KB - Last synced at: about 2 years ago - Pushed at: almost 8 years ago - Stars: 16 - Forks: 2

Kirill-Kravtsov/drophead-pytorch

An implementation of drophead regularization for pytorch transformers

Language: Python - Size: 13.7 KB - Last synced at: over 2 years ago - Pushed at: almost 4 years ago - Stars: 15 - Forks: 6

NewGround-LLC/psistats

Applying Deep Machine Learning for psycho-demographic profiling of Internet users using O.C.E.A.N. model of personality.

Language: R - Size: 4.71 MB - Last synced at: over 2 years ago - Pushed at: about 8 years ago - Stars: 15 - Forks: 3

danielkelshaw/ConcreteDropout

PyTorch implementation of 'Concrete Dropout'

Language: Python - Size: 399 KB - Last synced at: 6 months ago - Pushed at: over 1 year ago - Stars: 14 - Forks: 2

aurelio-amerio/ConcreteDropout

Concrete Dropout implementation for Tensorflow 2.0 and PyTorch

Language: Python - Size: 147 KB - Last synced at: about 1 month ago - Pushed at: 5 months ago - Stars: 13 - Forks: 4

deep-learning-algorithm/PyNet

Numpy implementation of deep learning

Language: Python - Size: 21.5 MB - Last synced at: over 1 year ago - Pushed at: almost 3 years ago - Stars: 13 - Forks: 4

anantSinghCross/realtime-hand-gesture-recognition

Hand Gesture Recognition using CNNs and Perceptrons in realtime (OpenCV)

Language: Python - Size: 38.6 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 13 - Forks: 11

the-lans/NeuroRepository

Фреймворк для построения нейронных сетей, комитетов, создания агентов с параллельными вычислениями.

Language: C++ - Size: 72.3 MB - Last synced at: about 1 year ago - Pushed at: almost 5 years ago - Stars: 11 - Forks: 8

ravi03071991/NIPS-Global-Paper-Implementation-Challenge

Selective Classification For Deep Neural Networks.

Language: Jupyter Notebook - Size: 193 KB - Last synced at: over 2 years ago - Pushed at: over 7 years ago - Stars: 11 - Forks: 3

ttungl/Deep-Learning

Implemented the deep learning techniques using Google Tensorflow that cover deep neural networks with a fully connected network using SGD and ReLUs; Regularization with a multi-layer neural network using ReLUs, L2-regularization, and dropout, to prevent overfitting; Convolutional Neural Networks (CNNs) with learning rate decay and dropout; and Recurrent Neural Networks (RNNs) for text and sequences with Long Short-Term Memory (LSTM) networks.

Language: Jupyter Notebook - Size: 1.86 MB - Last synced at: almost 2 years ago - Pushed at: over 7 years ago - Stars: 11 - Forks: 6

NinaadRao/Multilabel-Image-Classification-using-Contractive-Autoencoder

Implementing contractive auto encoder for encoding cloud images and using that encoding for multi label image classification

Language: Jupyter Notebook - Size: 17.8 MB - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 10 - Forks: 4

PooyaAlamirpour/TrafficSignClassifier

This project is an aspect of a big project that is called the Self-Driving Car. One of the essential techniques in Self-Driving Car engineering is detecting the Traffic Sign. In this project I have used Deep Learning for recognizing the Traffic Signs.

Language: Jupyter Notebook - Size: 5.38 MB - Last synced at: about 2 years ago - Pushed at: about 4 years ago - Stars: 9 - Forks: 6

DelTA-Lab-IITK/CD3A

Code for Curriculum based Dropout Discriminator for Domain Adaptation(CD3A), BMVC, 2019

Language: Lua - Size: 2.53 MB - Last synced at: 6 months ago - Pushed at: over 5 years ago - Stars: 9 - Forks: 4

gtesei/DeepExperiments

TensorFlow/Keras experiments on computer vision and natural language processing

Language: Jupyter Notebook - Size: 10.6 MB - Last synced at: about 2 months ago - Pushed at: over 6 years ago - Stars: 9 - Forks: 10

mabirck/adaptative-dropout-pytorch

Pytorch implementation of Adaptative Dropout a.ka Standout.

Language: Python - Size: 10.7 KB - Last synced at: about 2 years ago - Pushed at: over 7 years ago - Stars: 9 - Forks: 0

fau-masters-collected-works-cgarbin/dropout-vs-batch-normalization

Dropout vs. batch normalization: effect on accuracy, training and inference times - code for the paper

Language: TeX - Size: 2.25 MB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 8 - Forks: 1

ronaldseoh/bayesian-dl-experiments

Bayesian deep learning experiments

Language: Jupyter Notebook - Size: 171 MB - Last synced at: over 2 years ago - Pushed at: almost 5 years ago - Stars: 8 - Forks: 2

sushant1827/Fashion-Clothing-Classification

Kaggle Machine Learning Competition Project : In this project, we will create a classifier to classify fashion clothing into 10 categories learned from Fashion MNIST dataset of Zalando's article images

Language: Jupyter Notebook - Size: 6.59 MB - Last synced at: about 2 months ago - Pushed at: over 5 years ago - Stars: 8 - Forks: 3

ShaishavJogani/Neural-Network-Handwritten-Digit-classification

Two hidden layer Neural Network with 99% Accuracy. Dropout Regularization scheme is also implemented and available as an option. Please read the report for full implemantation Description.

Language: Python - Size: 40.7 MB - Last synced at: almost 2 years ago - Pushed at: about 6 years ago - Stars: 8 - Forks: 2

FrancescoCrecchi/DropIn-ESN

This repository contains the code used to produce the results presented in the IJCNN 2017 paper "DropIn: Making Reservoir Computing Neural Networks Robust to Missing Inputs by Dropout" by D. Bacciu, F. Crecchi (University of Pisa) and D. Morelli (Biobeats LTD).

Language: Matlab - Size: 28.3 KB - Last synced at: about 1 year ago - Pushed at: about 8 years ago - Stars: 8 - Forks: 1

CyberZHG/keras-drop-connect 📦

Drop-connect wrapper

Language: Python - Size: 12.7 KB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 7 - Forks: 4

iscience-kn/dropR

drop out analysis with R and shiny

Language: R - Size: 8.35 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 6 - Forks: 0

CyberZHG/keras-targeted-dropout 📦

Targeted dropout implemented in Keras

Language: Python - Size: 15.6 KB - Last synced at: 4 months ago - Pushed at: about 6 years ago - Stars: 6 - Forks: 4

Z7zuqer/DropBlock-Caffe

Implementation of DropBlock: A regularization method for convolutional networks in Caffe.

Language: C++ - Size: 12.7 KB - Last synced at: about 2 months ago - Pushed at: over 6 years ago - Stars: 6 - Forks: 0

RizwanMunawar/Cats-vs-dogs-classification-computer-vision-

Cats vs dogs classification using deep learning. Data augmentation and convolutional neural networks.

Language: Jupyter Notebook - Size: 1.57 MB - Last synced at: about 2 months ago - Pushed at: 4 months ago - Stars: 5 - Forks: 2

mroodschild/froog

neural network

Language: Java - Size: 79.6 MB - Last synced at: about 2 years ago - Pushed at: about 3 years ago - Stars: 5 - Forks: 0

turkdogan/dropout

A Simple dropout implementation in C++

Language: C++ - Size: 13.9 MB - Last synced at: 5 months ago - Pushed at: over 7 years ago - Stars: 5 - Forks: 1

dendisuhubdy/fraternal-nmt

Neural Machine Translation with Fraternal Dropout

Language: Python - Size: 108 KB - Last synced at: about 1 year ago - Pushed at: over 7 years ago - Stars: 5 - Forks: 1

sujatasaini/Kuzushiji-DropBlock

Japanese Handwritten Character Recognition using DropBlock Regulzarization

Language: Python - Size: 334 KB - Last synced at: about 2 years ago - Pushed at: about 4 years ago - Stars: 4 - Forks: 1

Tasiabueno/Bayesian-Convolutional-Neural-Network-Crack-Detection

A Bayesian Convolutional Neural Network approach for image-based crack detection and maintenance applications

Language: Jupyter Notebook - Size: 9.29 MB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 4 - Forks: 0

fraunhofer-iais/second-moment-loss

The second-moment loss (SML) is a novel training objective for dropout-based regression networks that yields improved uncertainty estimates.

Language: Jupyter Notebook - Size: 28.3 KB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 4 - Forks: 1

LaxmiChaudhary/SVHN-Deep-Neural-Network

Implementing an Image classification neural network to classify Street House View Numbers

Language: Jupyter Notebook - Size: 533 KB - Last synced at: 8 months ago - Pushed at: over 5 years ago - Stars: 4 - Forks: 12

kinoute/Elyane

An OOP Deep Neural Network using a similar syntax as Keras with many hyper-parameters, optimizers and activation functions available.

Language: Python - Size: 41.8 MB - Last synced at: 19 days ago - Pushed at: almost 6 years ago - Stars: 4 - Forks: 3

masoudshahrian/DeepLearning-Code

Deep learning Projects with code

Language: Jupyter Notebook - Size: 6.61 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 3 - Forks: 0

ahmadali-jamali/Convolution-Pooling-Dropout

Manual pure code of Convolution-Pooling-Dropout

Language: Python - Size: 354 KB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 0

JoshuaShunk/NSDropout

Language: Jupyter Notebook - Size: 1.89 MB - Last synced at: almost 2 years ago - Pushed at: about 3 years ago - Stars: 3 - Forks: 0

Arijit-datascience/CNN_BatchNormalization_Regularization

MNIST Digit Prediction using Batch Normalization, Group Normalization, Layer Normalization and L1-L2 Regularizations

Language: Jupyter Notebook - Size: 705 KB - Last synced at: almost 2 years ago - Pushed at: almost 4 years ago - Stars: 3 - Forks: 1

gianlucatruda/Spo2_evaluation Fork of CoVital-Project/Spo2_evaluation

Covid-19 | Quantifying Uncertainty in Blood Oxygen Estimation Models from Real-World Data

Language: Python - Size: 332 MB - Last synced at: 6 months ago - Pushed at: almost 5 years ago - Stars: 3 - Forks: 0

ashishpatel26/Regularization-Collection-Deeplearning

This is Collection of Regularization Deep learning techniques with code and paper

Size: 1.95 KB - Last synced at: 3 months ago - Pushed at: almost 5 years ago - Stars: 3 - Forks: 2

sharmaroshan/V2-Plant-Seedlings-Classification

It has 12 Classes for twelve different types of crops. This Dataset is in a zip file containing twelve folders of each plant containing their pictures. It is a Image Classification Problem, which can be easily solved Deep Learning Models such CNN(Convolutional Neural Networks)

Language: Jupyter Notebook - Size: 195 KB - Last synced at: over 1 year ago - Pushed at: almost 6 years ago - Stars: 3 - Forks: 1

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

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

Language: Jupyter Notebook - Size: 729 KB - Last synced at: about 2 years ago - Pushed at: over 6 years ago - Stars: 3 - Forks: 3

marcovirgolin/Uncertainty-Estimation-in-Deep-Nets

Attempt to reproduce the toy experiment of http://bit.ly/2C9Z8St with an ensemble of nets and with dropout.

Language: Python - Size: 91.8 KB - Last synced at: about 2 years ago - Pushed at: over 6 years ago - Stars: 3 - Forks: 1

mohamedkhayat/DIYNeuralNet

A lightweight deep learning framework implemented from scratch using NumPy/CuPy. supports customizable architectures, forward and back propagation, dropout, He/Glorot init, and mini-batch training. Designed for flexibility,it provides a foundation for building neural networks while giving insights into the inner workings of deep learning models

Language: Python - Size: 21.2 MB - Last synced at: 6 days ago - Pushed at: 6 days ago - Stars: 2 - Forks: 0