Learning Machine Learning with Aston

Before going to Caltech, we had narrowed down our ideas to one ambitious and one simpler project. The ambitious one was the e-cigarette image recognition system and the simpler one was going to be the game like tic-tac-toe. Upon getting to Caltech, though, our selection was pretty much dismissed as we went through all of our ideas with the graduate students. This was because Dr. Hassibi had to be in a meeting. Because we received further commentary on the other ideas, the visit really had us back to square one.  Some things I learned at Caltech exposed possible areas of weakness in our project ideas. The grad students pointed out that for the e-cigarette idea, we would need a lot of data, meaning that we would need a lot of examples of someone vaping in front of the thermal sensor. Robert explained that he saw a person train the image recognition algorithm with just 25 images. While the certainty wasn't great, the answer was typically correct. Because we are focusing on th...

After our visit to CalTech last Thursday, we narrowed down our semester 2 project ideas to the four that will be elaborated upon below. Before I do that, here's what I have been doing since last Thursday. First, I have been looking into current e-cigarette vapor sensors and how thermal imaging recognition works. I have also discussed the different project ideas with group mates and am working with Robert to focus on this more ambitious project. I am looking forward to exploring how to gather a dataset of thermal images for algorithm training and how effective our sensor would be. Idea 1: E-Cigarette Thermal Sensor Alert System One major issue that afflicts the youth of today is the use of e-cigarettes, wiping away remarkable progress in fighting smoking. This rise not only creates another issue for health professionals but issues in a new wave of modernization in our response to high-tech nicotine. Due to privacy laws, most students use use e-cigarettes in school restrooms and...

My first semester of Caltech STEM Research really exposed me to a lot of more in-depth concepts that I have come to really appreciate. Such concepts include the wide range of clustering algorithms, decision trees, recommender systems, and more. It felt very fulfilling to be exploring machine learning in a high school environment. For example, the iris decision tree project (depicted below) was quite different from my past interactions with computer science. We were actually making real-world deductions from the iris dataset and not just coding a game of battleship. The explorations of these concepts also enabled me to get to know my machine learning group mates better and working with them has also made the class a lot more fun and collaborative. A very useful skill I learned last semester was the screen capture video recording. This key aspect of my concept maps proved useful in creating a video in my Economics class and sending a video to Naviance regarding an issue. I also le...