Amazing AI Studio Online

10 1 10 1 123 1 1 9 12.3456 45 0 3.1 64 10 50 1 100 1 100 abc {textVariable} abc {textVariable} {textVariable} abc abc ｱｲｳｴｵ abc ab abc 5 {listVariable} {listVariable} {listVariable} 0 {listVariable} {listVariable} {listVariable} {listVariable} {listVariable} {listVariable} , {listVariable} brabra 100 50 0 xs Hello 0 0 1 1 2 2 2 2 1 0 9 10 0 9 5 2 5 2 3 categoricalCrossentropy 8 0.2 0.3 32 3 2 192 5 1 - - 2 2 2 0.01 0.01 32 1 4 0.45 0123456789 + 1 40 3 2048 0 Hello! 0 100 200 200 2 7 pointsOfFindContour SELECT IMAGE FALSE 200 200 resized grayscaled adaptive_filterd 2 7 find_contoured 4 100 0.05 10 warped resized image_element_id 100 TITLE program 123 0 0 100 100 10 20 255 10 #ff0000 0 2 150 message 0 0 48px serif message 30 30 20 10 50 50 30 10 10 20 20 10 20 0 0 100 100 0 0 0 0 100 100 0 0 75 DIVIDE 1 WIDTH 1 HEIGHT 1 10000 #ffffff 1 #ffffff 1 #ffffff 1 100 #ffffff 1 100 DIVIDE 1 PI 4 0 10 20 https://amazing-ai-studio.com/three/textures/land_ocean_ice.jpg 10 10 10 1 100 8 100 250 8 helvetiker_regular Hello! 100 10 #ffffff #ffffff #ffffff 0 0 0 0 0 0 0.01 renderer camera scene renderer renderer 2 camera 75 DIVIDE 1 WIDTH 1 HEIGHT 1 10000 camera position.z 1000 scene renderer scene camera abc 512 information Hello world! TITLE https://hooks.slack.com/services/xxx/xxx/xxx This is a text #cc0000 https://hooks.slack.com/services/xxx/xxx/xxx Training results. acc loss 90% 1% 0000180a-0000-1000-8000-00805f9b34fb 00002a24-0000-1000-8000-00805f9b34fb Hello! 100 C:/base/**/*.png orcl scott emp empno sal orcl scott emp orcl SELECT empno, sal FROM scott.emp https://www.google.com/ 1024 768 input[name=q] Amaiging AI Studio 0.5 input[name=btnK] input[name=btnK] 0.5 #file_01 C:/tmp/input. 0.5 input[name=btnK] 0.5 window.document.title = 'Hello world.'; 0.5

This demo shows how to perform classification on the classic Iris flower data set using two Dense Layers block.