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01:11:14 Lecture 13 (Second Part) Lecture 15 (First Part) Lecture 13 (Second Part) Lecture 15 (First Part)	Lecture 13 (Second Part) Lecture 15 (First Part) learning network things energy point transitions networks function landscapes machine water climate science thing layer layers lot cancer kind levels From John Rundle 0 likes 21 plays 0
36:21 GIS for River Science- Rasters, Part 2 GIS for River Science- Rasters, Part 2	GIS for River Science- Rasters, Part 2 This is part of a 4-hr, optional, casual training session for HYD254Y in which I am introducing students to GIS. I did not record the first 2 hours of the session, but then I did turn on the… hyd254y gis arcgis elevation points raster 3d tools thing point triangles model appearance surface coordinate things ground contours output shapefile layers dem hillshade From Gregory Pasternack 0 likes 3 plays 0
01:11:39 yi.ma.4.13 yi.ma.4.13	yi.ma.4.13 In this talk, we offer an entirely “white box’’ interpretation of deep (convolution) networks from the perspective of data compression (and group invariance). In particular, we show… network networks thing lot class layers things rate structure classes space question optimization channels convolution measure representation compression backpropagation layer From Stefan Schonsheck 0 likes 27 plays 0
44:55 EPS 131 Lecture 16 (Third Part) Lecture 17 EPS 131 Lecture 16 (Third Part) Lecture 17	EPS 131 Lecture 16 (Third Part) Lecture 17 EPS 131 Lecture 16 (Third Part) Lecture 17 atmosphere dioxide carbon layer kilometers eruption earth radiation lot valley ozone lake lava caldera stratosphere boundary eruptions yellowstone light layers From John Rundle 0 likes 6 plays 0
27:13 SSC107_2020_26_L13_M SSC107_2020_26_L13_M	SSC107_2020_26_L13_M flow water equation force pipe pressure velocity potential movement delta cylinder viscosity p2 volume soil p1 layers mu rate thing From Majdi Abou Najm 0 likes 50 plays 0
19:04 Discussion 10-30 Discussion 10-30	Discussion 10-30 network validation function layer neuron training model testing accuracy activation neurons values batch layers kind epochs width batches callback input From Dhruvatara Bhogishetty 0 likes 169 plays 0
48:54 ECS 150 - Lecture - OS Structure ECS 150 - Lecture - OS Structure	ECS 150 - Lecture - OS Structure application kernel library dot libraries executable memory process layer function laptop math loader kind processes layers microkernel idea stack fact From Joël Porquet-Lupine 0 likes 1,635 plays 0