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Multi-task Learning solves multiple tasks at one time, while exploiting commonalities and differences across tasks. Multi-modal Learning integrates and processes multiple types of data in one framework.
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How Chat-gpt from Open-AI going to affect our day-to-day work?
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This is a tutorial for analyzing audio MNIST (digits) dataset
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Notes for reading paper: learning and evaluating representations for deep one-class classification link.
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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.
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I here list some different challenges in data labels that I encountered in the past and ways to model them.
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This note summerizes using a simple and efficient trick: reverse gradient searching for finding turning points in noisy cases.
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TSlearn package for classic timeseries clustering methods.
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Notes from reading papers about Stochastic Block Models and Graph Neural Networks
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A simple tutorial on how to host a python service on a server using bat script and task scheduler.
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Ortogonal Matching Pursuit for recovering sparse signals