Week of 9.10

WEEK OF 9.10

We went to CalTech this Thursday! It was a pretty cool experience, since we got to see our professors for the first time. Dr. Hassibi took us to a room on campus, and we started to dip our toes into our understanding of machine learning. There were many aspects of learning that I hadn't known before, and I think that the session was pretty helpful. I also learned that learning isn't memorization, but actually generalization. That was pretty rad.

I worked on another paper airplane lab experiment. This time, we folded the tips of our three airplanes up, down, and straight forward. I wasn't surprised that the one with the up folded tip did the best since I knew already that it reduced a lot of drag. It was still pretty neat having my ideas confirmed and validated by the data though.

You really just can't compete with the beauty and the amazing-ness of our plane. It's folded rather precisely and it flies excellently as well. 

Look at us flying the planes! I think our machine learning group is the best research out of all the groups. Not only do we lead the way and personalize our learning experience (looking @ you, Mr. Lee), but we actually can have fun and joke around with each other. I think that's incredibly valuable when we're all working and learning together. I think all the other groups are actually a little bit secretly jealous of us. We actually enjoy what we do and we have the creative capacity to imagine. I'm not saying the other groups suck, but what I'm saying is that our group is pretty rad. You can't really beat it. 

We started learning linear regression. The math parts are pretty tedious, but I think overall I can understand the concepts and be able to GENERALIZE that information in the concept maps. At least if I'm having trouble I can ask my group for help since we're (finally) learning together. That will help me a lot and I think that'll help the rest of the people in my group out too. We're all in this together!

Here is a picture of us figuring out the derivative. A lot of the board isn't actually part of the math, but that's okay because we still learned about/reviewed what a derivative was and its application in the context of gradient descent. Overall pretty cool.

On Monday we reviewed the goals and expectations of the course. Mr. Lee gave us this slideshow presentation detailing his perspective on the class's approach to learning.

We went to CalTech again- this time we learned about K-means clustering and learning. I think that the sessions we go to CalTech for are pretty informative and helpful, and overall I think I'm learning a lot from it. It's not too difficult to understand, but I'm certain that we're going slow and steady with this.