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2020-zhihuihaiyang

2020数字**创新大赛-数字政府赛道-智能算法赛：智慧海洋建设算法赛道代码

anomaly-detection

Anomaly detection is a common problem that is applied to machine learning/deep learning research. Here we will apply an LSTM autoencoder (AE) to identify ECG anomaly detections. In our experiments, anomaly detection problem is a rare-event classification problem. Therefore we will train our LSTM AE with major class, then we would have a higher mean squared error when model sees a minor class in the dataset.

awesome-multimodal-ml

Reading list for research topics in multimodal machine learning

cellvgae

An unsupervised scRNA-seq analysis workflow with graph attention networks

chinese-sequence-ner

chinese-sequence-ner多模型中文命名实体识别

flowmap

Simple tools for visualizing geometries, flows and trajectories.

lstm_anomaly_thesis

Anomaly detection for temporal data using LSTMs

pyculiarity

A Python port of Twitter's AnomalyDetection R Package

pythoncoursecode

python course code for bigdata

research_spatio-temporal-data-mining

A collection of research on spatio-temporal data mining

springboot-course-demo

stgcn

implementation of STGCN for traffic prediction in IJCAI2018