Introduction For those who have been affiliated with UTMIST for a long time, you’re probably aware that we’ve previously published all articles from the technical writing department on our Medium account. Of course, the writer would always be given credit, but this really limited the scope of what the technical writing…

A UTMIST Project by Jack Cai, Lisa Yu, Younwoo (Ethan) Choi, Dongfang Cui, Alaap Grandhi, Demetre Jouras, Kevin Mi, Yang Qu, Zhenhai (Joel) Quan, Thomas Verth. The Wall Street Bots project is a 6-month challenge to build a stock trading platform utilizing data analysis and machine learning methods. The final…

A UTMIST Project by Hanni Ahmed, Maanas Arora, Nabil Mohamed, Thomas Zeger, (Timothy Kwong), and Yan Zhu. Introduction Cardiovascular disease (CVD) is the leading cause of death in the world. According to the World Health Organization, about 17.9 million people died from CVDs in 2019, representing 32% of all global deaths…

A UTMIST Project by Justin Tran, Fernando Assad, Kiara Chong, Armaan Lalani, and Eeshan Narula. Introduction Recognizing handwritten text is a long-studied problem in machine learning, with one of the most well-known datasets being the MNIST [1] for handwritten digits. While recognizing individual digits is a solved problem, scientists have been…

A UTMIST Project by Maliha Lodi, Afnan Rahman, Kevin Qu, Omer Raza Khan, Yinan Zhao, and Matthew Zhu. Project Overview An organization is only as good as its employees, as they provide the company with its competitive advantage. As a result, it is imperative that companies understand how to retain their top…

A UTMIST Project by Arsh Kadakia, Sepehr Hosseini, Matthew Leung, Arahan Kadakia, and Leo Li RealTime is a machine learning project for predicting home prices in the GTA. It is a significant improvement on last year’s project, RealValue, by focusing on more data than ever before. Thanks to the effective…

A UTMIST Project by Noah Cristino, Bradley Mathi, Daniel Zhu, and Mishaal Kandapath. Smile Detector detects smiles in images using a new multi-step approach, which consists of performing facial recognition and then running the detected facial vectors through our custom C-Support Vector Classification model. By reducing the model input size…

Written by Charles Yuan. A discussion on the paper title “Adaptive Aggregation Networks for Class-Incremental Learning”. Introduction When you really think about it, deep learning algorithms are fundamentally restricted from achieving true artificial general intelligence. For those who have ever constructed and trained a neural network, you would likely be familiar…

Written by Natalie Volk. A discussion on the paper title “Causal Inference in medicine and in health policy”. Causal inference is a major area of research in machine learning, aiming to incorporate an understanding of cause-and-effect into AI models. By doing so, researchers believe that machine learning can help improve…