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53 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）

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

Neural Structured Learning ⭐ 972

Training neural models with structured signals.

Caffe for Sparse and Low-rank Deep Neural Networks

Neural Collaborative Filtering ⭐ 312

pytorch version of neural collaborative filtering

Machine Learning Notebooks ⭐ 241

Machine Learning notebooks for refreshing concepts.

Hipsternet ⭐ 222

All the hipster things in Neural Net in a single repo

Python Tensorflow Google ⭐ 176

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

Machine_learning_2018 ⭐ 146

Codes and Project for Machine Learning Course, Fall 2018, University of Tabriz

Deep Learning Specialization Coursera ⭐ 92

Deep Learning Specialization courses by Andrew Ng, deeplearning.ai

Deep Learning Explained ⭐ 68

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

Lstmkf_iccv2017 ⭐ 63

Long Short-Term Memory Kalman Filters: Recurrent Neural Estimators for Pose Regularization

Adaptive Regularization Neural Network ⭐ 59

[NeurIPS'19] [PyTorch] Adaptive Regularization in NN

Deep Learning 101 ⭐ 56

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

Artificial Neural Networks With Jupyter ⭐ 41

Artificial Neural Networks - Gradient descent, BFGS, Regularization with Jupyter notebook

The Deep Learning With Keras Workshop ⭐ 40

An Interactive Approach to Understanding Deep Learning with Keras

Deeplearning Padhai ⭐ 39

All the code files related to the deep learning course from PadhAI

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.

Deeplearning.ai ⭐ 36

deeplearning.ai

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

OICSR: Out-In-Channel Sparsity Regularization for Compact Deep Neural Networks

Stux Dnn ⭐ 21

Run-time trojan attack on neural networks

Implementation of "Effective Adversarial Regularization for Neural Machine Translation", ACL 2019

Deep Learning Topics ⭐ 18

Certifiedmonotonicnetwork ⭐ 17

SANNet Neural Network Framework

Morph.py ⭐ 16

A neural architecture optimizer, targeted at model-size w.r.t. accuracy

Deep Learning Notes ⭐ 15

Deep Learning Coursera Specialization • Lecture Notes • Lab Assignments

Machine_learning_from_scratch ⭐ 15

Machine Learning models from scratch with a better visualisation

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

Nn Dropout ⭐ 14

This code is for training feedforward neural networks with dropout.

Deeplearning_models_classifier_tutorial ⭐ 12

使用常见的CNN架构实现CIFAR分类。

Manifold_mixup ⭐ 12

Tensorflow implementation of the Manifold Mixup machine learning research paper

Learning Class Invariant Features ⭐ 11

Repository for the code of the paper "Neural Networks Regularization Through Class-wise Invariant Representation Learning".

Prior Knowledge Integration for Neural Machine Translation using Posterior Regularization

Deeplearning_ai_books ⭐ 10

黄海广博士整理的【吴恩达】深度学习笔记

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

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

User2016 Notes ⭐ 8

Notes for tutorials and sessions at useR! 2016 Conference 📝

Ffjord Rnode ⭐ 8

Regularized Neural ODEs (RNODE)

Google Ml Bootcamp ⭐ 8

구글 머신러닝 부트캠프 - 관련 파일 자료 (과제 번역 포함)

Improving Deep Neural Networks ⭐ 7

Improving-Deep-Neural-Networks

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.

Machine_learning ⭐ 7

Machine Learning - Coursera.org

Machine Learning ⭐ 7

Andrew Ng's Machine Learning Course

Dynamical Isometry From Orthogonality Neural Nets ⭐ 6

Mathematical consequences of orthogonal weights initialization and regularization in deep learning. Experiments with gain-adjusted orthogonal regularizer on RNNs with SeqMNIST dataset.

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.

Neural Classifier ⭐ 5

My attempt to write classification library based on neural networks.

Stochastic Computing for Deep Neural Networks

Structured Output Ae ⭐ 5

Repository for the code of the paper "Deep Neural Networks Regularization for Structured Output Prediction"

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