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Type: Organization
Type: Organization
Holistically-Nested Edge Detection in Keras
Implementation of paper: Making Deep Neural Network Robust to Label Noise: a Loss Correction Approach.
Official Implementation of ICML 2019 Unsupervised label noise modeling and loss correction
Code for CVPR 2016 paper on Learning from Noisy Labels
A meta-learning setup to utitlize the unlabeled data for target task. An implementation of "Learning to learn from weak supervision by full supervision". https://arxiv.org/abs/1711.11383
PyTorch code for CVPR 2018 paper: Learning to Compare: Relation Network for Few-Shot Learning (Few-Shot Learning part)
Oxford Deep NLP 2017 course
A Light CNN for Deep Face Representation with Noisy Labels, TIFS 2018
《统计学习方法》的代码实现
LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data
机器学习初学者公众号作品
Code for MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks
Meta-Learning based Noise-Tolerant Training
Generating longer musical pieces with an RNN-RBM in TensorFlow
A repository for some code about music generating neural networks
复盘所有NLP比赛的TOP方案,只关注NLP比赛,持续更新中!
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
YSDA course in Natural Language Processing
This is a collection of Papers and Codes for Noisy Labels Problem.
Code for the CVPR15 paper "Learning from Massive Noisy Labeled Data for Image Classification"
TRAINING DEEP NEURAL-NETWORKS USING A NOISE ADAPTATION LAYER
Code for the paper "Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks"
PANet for Instance Segmentation and Object Detection
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Papers with code. Sorted by stars. Updated weekly.
Using the CLR algorithm for training (https://arxiv.org/abs/1506.01186)
CurriculumNet: Weakly Supervised Learning from Large-Scale Web Images
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.