A podcast featuring panelists of engineers from Netflix, Twitch, & Atlassian talking over drinks about all things software engineering.
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Indhold leveret af Carl Franklin and Richard Campbell, Carl Franklin, and Richard Campbell. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Carl Franklin and Richard Campbell, Carl Franklin, and Richard Campbell eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
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Machine Learning on Geospatial Data with Malte Loller-Anderson & Mathilde Ørstavik
MP3•Episode hjem
Manage episode 436743450 series 134848
Indhold leveret af Carl Franklin and Richard Campbell, Carl Franklin, and Richard Campbell. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Carl Franklin and Richard Campbell, Carl Franklin, and Richard Campbell eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
What can machine learning do for geospatial data? Carl and Richard talk to Malte Loller-Anderson and Mathilde Ørstavik about their work at Norkart, using aerial imagery to build detailed maps around Norway. Mathilde dives into the critical role of machine learning - identifying buildings in images. Usually done by hand with each new image, Norkart has a machine learning model that automates the process trained on previous vector maps of buildings. But there are many things that look like buildings in Norway, including patches of snow, mountains, and even shapes under water. Malte also discusses how Norkart has decided to train in-house with nVidia L40 processors rather than in the cloud - the hardware is used 24 hours a day since some models can take weeks to train! There are many interesting ideas about geospatial data and machine learning from people who have been doing it for years.
…
continue reading
556 episoder
MP3•Episode hjem
Manage episode 436743450 series 134848
Indhold leveret af Carl Franklin and Richard Campbell, Carl Franklin, and Richard Campbell. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Carl Franklin and Richard Campbell, Carl Franklin, and Richard Campbell eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.
What can machine learning do for geospatial data? Carl and Richard talk to Malte Loller-Anderson and Mathilde Ørstavik about their work at Norkart, using aerial imagery to build detailed maps around Norway. Mathilde dives into the critical role of machine learning - identifying buildings in images. Usually done by hand with each new image, Norkart has a machine learning model that automates the process trained on previous vector maps of buildings. But there are many things that look like buildings in Norway, including patches of snow, mountains, and even shapes under water. Malte also discusses how Norkart has decided to train in-house with nVidia L40 processors rather than in the cloud - the hardware is used 24 hours a day since some models can take weeks to train! There are many interesting ideas about geospatial data and machine learning from people who have been doing it for years.
…
continue reading
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