Predicting weather with deep learning

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F23%3A00375863" target="_blank" >RIV/68407700:21240/23:00375863 - isvavai.cz</a>

Result on the web

<a href="https://www.mlprague.com/prague2023/" target="_blank" >https://www.mlprague.com/prague2023/</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Predicting weather with deep learning

Original language description

In this workshop we will implement train and test machine learning models that analyze satellite and weather radar data. You will get hands-on experience with the most common deep neural nets used for spatiotemporal predictions (e.g. UNet with some bells and whistles and convolutional recurrent nets). You will play with PyTorch implementation and analyze the results. You will understand the common pitfalls and reasons why the prediction fails.

Czech name

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Czech description

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Type

W - Workshop organization

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Event location

Praha

Event country

CZ - CZECH REPUBLIC

Event starting date

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Event ending date

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Total number of attendees

60

Foreign attendee count

50

Type of event by attendee nationality

WRD - Celosvětová akce