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regularization x

51 search results found

Deeplearning_ai_books ⭐ 14,417

deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）

Mxnet The Straight Dope ⭐ 2,507

An interactive book on deep learning. Much easy, so MXNet. Wow. [Straight Dope is growing up] ---> Much of this content has been incorporated into the new Dive into Deep Learning Book available at https://d2l.ai/.

Coursera Deep Learning Specialization ⭐ 2,459

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

Morph Net ⭐ 1,010

Fast & Simple Resource-Constrained Learning of Deep Network Structure

Cifar Zoo ⭐ 575

PyTorch implementation of CNNs for CIFAR benchmark

Dropblock ⭐ 408

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

Deep Learning Tricks ⭐ 381

Enumerate diverse machine learning training tricks.

Dmn Tensorflow ⭐ 235

Dynamic Memory Networks (https://arxiv.org/abs/1603.01417) in Tensorflow

Python Tensorflow Google ⭐ 176

Notes taken from Google Machine Learning Course provided to public for practice & correction.

Deep Learning Specialization Coursera ⭐ 92

Deep Learning Specialization courses by Andrew Ng, deeplearning.ai

[NeurIPS'20] GradAug: A New Regularization Method for Deep Neural Networks

Deep Learning Explained ⭐ 68

This repository contains the lab files for Microsoft course DAT236x: Deep Learning Explained

Iss Rnns ⭐ 62

Sparse Recurrent Neural Networks -- Pruning Connections and Hidden Sizes (TensorFlow)

Deep Learning 101 ⭐ 56

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

Sparsebn ⭐ 37

Software for learning sparse Bayesian networks

Deeplearning.ai ⭐ 36

deeplearning.ai

Deep Learning Specialization Coursera ⭐ 36

Deep Learning Specialization Course by Coursera. Neural Networks, Deep Learning, Hyper Tuning, Regularization, Optimization, Data Processing, Convolutional NN, Sequence Models are including this Course.

Adversarial Robustness Public ⭐ 30

Code for AAAI 2018 accepted paper: "Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients"

Numpy_neural_net ⭐ 24

A simple neural network (multilayer perceptron) with backpropagation implemented in Python with NumPy

Traj Pred Irl ⭐ 23

Official implementation of "Regularizing neural networks for future trajectory prediction via IRL framework" published in IET CV

Stux Dnn ⭐ 21

Run-time trojan attack on neural networks

Deep Learning Topics ⭐ 18

Multi Label Classification ⭐ 18

基于tf.keras的多标签多分类模型

Deepmesh ⭐ 18

Random Mesh Projectors for Inverse Problems

Certifiedmonotonicnetwork ⭐ 17

SANNet Neural Network Framework

An implementation of "Fusing Structure and Content via Non-negative Matrix Factorization for Embedding Information Networks".

Implementation for <Regularizing Neural Networks via Minimizing Hyperspherical Energy> in CVPR'20.

Deeplearning_models_classifier_tutorial ⭐ 12

使用常见的CNN架构实现CIFAR分类。

Traffic Sign Cnn ⭐ 12

Deep learning network for traffic sign image classification

📊 Generalized linear regression models with network-regularization in R.

Netnmf Sc ⭐ 10

netNMF-sc: A network regularization algorithm for dimensionality reduction and imputation of single-cell expression data

Deeplearning_ai_books ⭐ 10

黄海广博士整理的【吴恩达】深度学习笔记

Deepexperiments ⭐ 9

TensorFlow/Keras experiments on computer vision and natural language processing

Neuralnetwork ⭐ 9

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

Deepadverserialregulariser ⭐ 9

Neural Networks And Deep Learning ⭐ 9

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

Google Ml Bootcamp ⭐ 8

구글 머신러닝 부트캠프 - 관련 파일 자료 (과제 번역 포함)

Comparatornetwork_pytorch ⭐ 8

This repo implements VGG's Comparator Network [1].

Dmn Chatbot ⭐ 7

Chat bot using Dynamic Memory Network

Deep Learning ⭐ 7

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.

Facebook Network Analysis Big5 Personality ⭐ 6

Analyzed users’ Big 5 personality traits to predicting network centrality within organic Facebook friend networks using linear regression with lasso regularization and k-folds cross validation.

Interp_regularization ⭐ 6

A novel neural network gradient regularization scheme for adversarial robustness and interpretability.

A C++ deep learning library for the construction and optimization of neural networks ranging from simple feedforward architectures to state-of-the-art convolutional ResNets and LSTMs.

Dropblock Keras Implementation ⭐ 5

Paper Reproduction: "DropBlock: A regularization method for convolutional networks"

Ccdralgorithm ⭐ 5

Structure learning for Bayesian networks using the CCDr algorithm.

Neural Classifier ⭐ 5

My attempt to write classification library based on neural networks.

Stochastic Computing for Deep Neural Networks

Keras Dropblock ⭐ 5

DropBlock:A regularization method for convolutional networks

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