Week One

We have officially completed week one! I didn’t know what to expect coming into this program so I prepared by doing the Coursera Machine Learning course by Andrew Ng. That course is no joke at all! He jumps right into supervised/unsupervised learning, cost function, hypothesis. When the easiest thing you cover is linear algebra you know it’s serious work.

Before the official first day I spent the night reading the provided articles to try to get some background knowledge on Machine Learning. The first article I read was eye opening! A few of the things in there I had heard about but I had no idea how useful machine learning could be in agriculture. The concept of a drone being able to identify weeds and spray them with pesticide blows my mind and my wife was shocked to hear about Pinterest Lens. We had no idea that existed!

Our first presenter was Mr. Ashutosh Sabharwal and he told us about his research into Sociability. His research showed that there might be a correlation between how sociable one is (the amount daily steps taken, average text message length, and the amount of text messages) and depression.

Our second presenter Souptik showed us how machine learning could improve the people self-manage diabetes.  I didn’t realize how uninformed I was about living with diabetes. The fact that a person can get an inaccurate glucose reading depending on the time they took a sample is a little bit scary to me. Luckily with Souptiks research hopefully he can help change that!

Last but not least we finished off the week with a presentation from Mr.Gerard L. Cote from A&M who talked to us about the idea of having cheap, easy to wear, reliable tech that can take readings from patients without them having to drive to a hospital. It really is timely seeing as this quarantine period has made face to face appointments risky!

This week was extremely rewarding and I already moved 2 articles into my teaching folder so I can use them with my class this fall! Very excited to see what else we learn from this program! 👊