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Challenges in data labels

Challenges in data labels

less than 1 minute read

Published:

I here list some different challenges in data labels that I encountered in the past and ways to model them.

Communities detection

Cosine similarity

Graph Neural Networks

LSTM

Predict unit-level LoS using time-series modelling

3 minute read

Published:

We propose to a dynamic, real-time, lightweight, end-to-end next day median ED-LoS prediction algorithm using time-series LSTM modelling. Similar method can be extended to unit-level KPI prediction.

Signal processing

Sparsity ML

Stochastic Block Models

Windows

audio signal processing

automatic start

bat

category1

category2

classification

clustering

contrastive learning

cool posts

dynamic time wrapping

gradient zero crossings

k-means

one-class classification

predictive model

Predict unit-level LoS using time-series modelling

3 minute read

Published:

We propose to a dynamic, real-time, lightweight, end-to-end next day median ED-LoS prediction algorithm using time-series LSTM modelling. Similar method can be extended to unit-level KPI prediction.

signal processing

task scheduler

time series

Predict unit-level LoS using time-series modelling

3 minute read

Published:

We propose to a dynamic, real-time, lightweight, end-to-end next day median ED-LoS prediction algorithm using time-series LSTM modelling. Similar method can be extended to unit-level KPI prediction.

turning points detection

unit-level Length of Stay(LoS)

Predict unit-level LoS using time-series modelling

3 minute read

Published:

We propose to a dynamic, real-time, lightweight, end-to-end next day median ED-LoS prediction algorithm using time-series LSTM modelling. Similar method can be extended to unit-level KPI prediction.

unsupervised learning