/docs/grading/project-breakdown/ Recent content in Project Breakdown on Class Homepage Hugo -- gohugo.io en-us /docs/grading/project-breakdown/proposal/ Mon, 01 Jan 0001 00:00:00 +0000 /docs/grading/project-breakdown/proposal/ Proposal (5%) # The primary goal of the proposal is to identify a problem that can be solved with machine learning. This includes finding and/or creating a dataset as well as developing a plan for the semester. Note: As part of research, it is natural that the project may change from the original proposed. Please be sure to document and justify these changes in the midterm and final report. /docs/grading/project-breakdown/midterm/ Mon, 01 Jan 0001 00:00:00 +0000 /docs/grading/project-breakdown/midterm/ Midterm Checkpoint (10%) # This is a checkpoint to make sure that you have had major progress in your project. By this point, at least one machine learning model should be implemented and evaluated. Results should be presented using visualizations and quantitative metrics. You will add information to your proposal to create your midterm report. Note: As part of research, it is natural that the project may change from the original proposed. /docs/grading/project-breakdown/final/ Mon, 01 Jan 0001 00:00:00 +0000 /docs/grading/project-breakdown/final/ Final Report (15%) # The final report should present and compare at least 3 models that you have developed throughout the semester. Results should be presented using visualizations and quantitative metrics with a heavy focus on comparing the performance and tradeoffs of each approach. You will add information to your midterm to create your final report. Note: As part of research, it is natural that the project may change from the original proposed. /docs/grading/project-breakdown/award_galore/ Mon, 01 Jan 0001 00:00:00 +0000 /docs/grading/project-breakdown/award_galore/ Why Awards Matter # Awards serve as a tangible recognition of the dedication and creativity students bring to their machine learning projects. Each semester, these select honors are chosen from among hundreds of submitted projects, making the competition fierce and underscoring the ingenuity and motivation of participating teams. By highlighting outstanding work, we encourage students to push boundaries, refine technical skills, and communicate findings more effectively. This recognition also benefits students’ academic and professional growth—award recipients can feature their projects on resumes and link directly to showcased work for added visibility.