*Errata:* I noticed an unfortunate typo on the results slide at 13:12 immediately after uploading the video! The posterior probability for Lime should read *2.18E-11* -- hence the classifier's first choice was an apple and its second choice was a lemon. A value of 2.18E-10 would result in the correct classification of "Lime." Sorry for the confusion!
Thanks! These types of devices serve two purposes - 1.) they are great for teaching/learning since the setup is relatively easy, self-contained and cheap (especially considering that it has a GPU, and 2.) they are good for “edge computing” purposes (such as putting it in a robot, for example), where a traditional computer would be too large and/or power hungry. Hope this helps!
*Errata:* I noticed an unfortunate typo on the results slide at 13:12 immediately after uploading the video! The posterior probability for Lime should read *2.18E-11* -- hence the classifier's first choice was an apple and its second choice was a lemon. A value of 2.18E-10 would result in the correct classification of "Lime." Sorry for the confusion!
Great video! I’m new to AI, so I’m wondering: if using your computer had equivalent or superior performance to the Jetson, why use the Jetson? Thanks!
Thanks! These types of devices serve two purposes - 1.) they are great for teaching/learning since the setup is relatively easy, self-contained and cheap (especially considering that it has a GPU, and 2.) they are good for “edge computing” purposes (such as putting it in a robot, for example), where a traditional computer would be too large and/or power hungry. Hope this helps!
Thanks for the easy to understand introduction.
Great video!
Thank you, James!
You look like a cyborg with your left eye 😂 the light is soo bright
🤖🤖🤖
Great video Learn a lot 👍 ty man
Pape Demba B. Ndiaye Thank you so much! Glad you liked it and found it useful! 😁