Building and Evaluating the Model: Machine Learning I – Non-Coding (Pre-hackathon Workshop)

CUHK Data Hack 2025 Pre-hackathon Workshop

* This workshop ONLY opens to CUHK community who have registered to join the CUHK Data Hack 2025*

Instructor: Dr. Michael YU, Department of Computer Science and Engineering, CUHK

A model aims to explain the patterns found in data. In data analysis, one primary goal is to systematically uncover these patterns. For these patterns to be practically useful, they must be integrated into a model.

Most AI systems rely on a variety of machine learning approaches tailored for specific tasks, allowing them to analyze vast datasets efficiently. With AI becoming increasingly pervasive in our society, we now have access to numerous toolkits designed for individuals who wish to apply machine learning, even without programming experience.

In this hands-on workshop, we will explore several common machine learning models and demonstrate how to build them using a no-code or minimal coding approach. Students will have the opportunity to engage in an alternative method for constructing and deploying machine learning models that are accessible to everyone. Following this, we will also examine non-coding toolkits that assess model performance, which is essential for evaluating effectiveness and pinpointing areas for improvement.