Hi Jeremy, I too want to say thank you, even though I have only started with the material. Your philosophy on how to teach the subject I feel will be much more

Hi Jeremy, I too want to say thank you, even though I have only started with the material. Your philosophy on how to teach the subject I feel will be much more useful to me than the classes I was signed up for recently (and lost interest in rather quickly). It's a lot easier to get excited about the practical things surrounding the topic which is why I'm looking forward to diving into the new content. On a related note, one thing I do see a heavy emphasis on with the material is on the Computer Vision / Image Processing side of things which is certainly understandable considering how popular that area is specifically right now. Something not really computer vision related though that I'm curious about (and I'm not sure if it's covered in the new/existing lessons) would be on how to craft a data set using data I might have accessible to me, but which isn't necessarily image-based, and to apply these techniques to that sort of data set to come up with predictions (I bring this up, because one of the goals I have for learning about this topic specifically is to see how I might be able to apply it back to my job at a community college and if I can pull historical data related to our students and use that for forecasting / recommendation purposes and create some useful applications our students can utilize...as a simple idea one example would be using historical data about the current student, and maybe data from other similar students, to predict success in a student's upcoming courses). Thank you and keep up the awesome work (and for sharing it freely :-)!