Machine Learning
Classification, regression, model selection, and evaluation that actually holds up.
Workshops, reading groups, research talks, and project teams for students exploring AI, machine learning, and data science.
Mission
We focus on practical systems: data quality, evaluation, iteration loops, and shipping workflows. Members learn by building and reviewing each other’s work.
Focus Areas
Classification, regression, model selection, and evaluation that actually holds up.
Prompting, retrieval, fine-tuning basics, safety, and practical app patterns.
Dataset curation, labeling workflows, vector search, and instrumentation.
Projects
Taught by Tech Lead David Card.
How to source, clean, document, and evaluate datasets for real training runs.
Get Involved →A retrieval-augmented assistant that answers from curated notes and papers.
Join the Team →Weekly breakdowns of new models, benchmarks, and what matters in practice.
Attend a Session →Repeatable experiments, metrics dashboards, and cost/latency tracking.
Contribute →Officers
President
Vice President
Tech Lead
Treasurer
Event Executive
Secretary
Design Director
Project Executive
Marketing Director
Networking Director
Join
Email us to get onboarded, or come to the next meeting.
Community
Faculty Advisor
ISSIP AI Collab Lead
Faculty Advisor
IDiyas, Chief Mentor
Mentor
Mentor
Mentor