[Solved] CS3120 Final Project: Self-determined Topic

2. Code Requirement and Evaluation 10pts:

Failure of running or downloading the code will result in a zero score for code evaluation. Code included in the submission should be ready to run, with proper relative path and necessary input files submitted or linked (Github links to your input datasets are acceptable when your dataset is huge.).

Well organized code with comments in it is the most important factor that determines the grade. (Jupyter notebook users need to submit your code in .py and make sure it is runnable on different platforms.)

Students are responsible for failure of running/downloading your code. Please include other support files that are helpful in grading in your full submission.

The project should NOT be evaluated by the performance (low or high accuracy) of the model. The credits are given based on how well your idea is developed or implemented, how much work is shown to be your own effort and how meaningful your work is.

3. Presentation Evaluation (Peer review) 10pts:

Each student needs to record a 4-minutes (or less) long presentation video, upload the video Here, watch and evaluate all the students presentations.

The average score will be used as the final presentation grade. Students who did not submit the video presentation to this link before deadline are considered as giving up this 10pts for presentation.

Format: Lastname_Firstname.mp4

About the content of your video: You can record your face or your screen or both. Make sure clearly explain what you did (the topic), what model you used, performance of your model and which part is your own work.

Link to upload your presentation video. Here

Link to evaluate all the presentations. Here

(Please do NOT evaluate other students presentations multiple times. Repeated evaluation scores from the same student will be deleted.)

Submission:

Part 1

• Report to blackboard

FinalProject_Lastname_Firstname.pdf/doc.

• A compressed file of all source code, .py files to blackboard
• A compressed file or a GitHub link of input dataset and output files (if any) to blackboard
• Other files you think that helps grading (e.g. readme.txt) to blackboard