In my last blog post, I detailed the implementation of machine learning models in iOS applications using the Core ML and Vision frameworks. As you probably remember from the tutorial, I implemented the Inception v3 model to give the app the ability to classify 1,000 common objects in the world. While it is true that you can easily download the model from a Github repository, have you ever wonder where it came from? In this blog post, I will introduce the “brain” behind the Inception v3 model––an artificial neural network (ANN).
As the holiday season approaches, my independent study on Game Theory is also coming to an end. In my last post, I would like to take the opportunity to reflect on my work with Game Theory this past semester, some lessons I’ve learnt, and my plan for the coming weeks. Continue reading
My independent project for this semester aims to create a report which compares several of the usual deep learning architectures using a set of grocery pictures. I started by watching and reading through open course materials and videos, which I found on the website of Stanford University, course CS231n. I also got in touch with a mentor from my hometown and sought his guidance on this topic. He is a graduate student at Fudan University, Shanghai. We arranged meetings every other week via Zoom and he has been helping me to better understand open course materials. Continue reading
Today, I’m going to introduce you to a new form of game different from all the games I’ve mentioned in my previous posts! Today, we are going to play a sequential game!
What is a sequential game? How is it different? Continue reading
Recently, I have been experimenting with CoreML, the machine learning framework for Apple’s mobile and desktop operating systems. Rather than continue my discussion of linear regression, I will detail the implementation of a model with CoreML in this blog post.