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Data augmentation using synthetic data for time series classification with deep residual networks
Anomaly detection related books, papers, videos, and toolboxes
A curated list of awesome anomaly detection resources
A curated list of community detection research papers with implementations.
A curated list of data mining papers about fraud detection.
List of tools & datasets for anomaly detection on time-series data.
This curated list contains python packages for time series analysis
Transfer learning for time series classification
Code of NIPS18 Paper: BRITS: Bidirectional Recurrent Imputation for Time Series
List of papers, code and experiments using deep learning for time series forecasting
DeepTables: Deep-learning Toolkit for Tabular data
Deep Learning models for network traffic classification
Deep Learning for Time Series Classification
The Model Zoo of Cognitive Diagnosis Models, including classic Item Response Ranking (IRT), Multidimensional Item Response Ranking (MIRT), Deterministic Input, Noisy "And" model(DINA), and advanced Fuzzy Cognitive Diagnosis Framework (FuzzyCDF), Neural Cognitive Diagnosis Model (NCDM) and Item Response Ranking framework (IRR).
Multivariate imputation and matrix completion algorithms implemented in Python
FOST is a general forecasting tool, which demonstrate our experience and advanced technology in practical forecasting domains, including temporal, spatial-temporal and hierarchical forecasting. Current general forecasting tools (Gluon-TS by amazon, Prophet by facebook etc.) can not process and model structural graph data, especially in spatial domains, also those tools suffer from tradeoff between usability and accuracy. To address these challenges, we design and develop FOST and aims to empower engineers and data scientists to build high-accuracy and easy-usability forecasting tools.
Implementation of gMLP, an all-MLP replacement for Transformers, in Pytorch
A robot powered training repository :robot:
Gated Recurrent Unit with a Decay mechanism for Multivariate Time Series with Missing Values
Deep Neural Network Ensembles for Time Series Classification
Curated List of papers on Time Series Analysis
Build a LSTM encoder-decoder using PyTorch to make sequence-to-sequence prediction for time series data
Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.
Multivariate LSTM Fully Convolutional Networks for Time Series Classification
Multi-NILM: Multi Label Non Intrusive Load Monitoring
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
Technically-oriented PDF Collection (Papers, Specs, Decks, Manuals, etc)
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.