vynx1 / student_csp

A cummilative project consisting of work in my AP Computer Science Principal Class. Acts as a personal blog and storage for various coding projects such as AI Flappy Bird.
MIT License
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Data Structure Writeup Peer Review #8

Open YeongsuKimm opened 2 months ago

YeongsuKimm commented 2 months ago

1.87 + 0.3(machine learning) /2 ==> 1.9/2 The rest of the code was working and was well-organized. Additionally, the Postman portion wasn't completed, which lost some points. However, the elements that were completed were done with accuracy and thoroughness. Also, there were detailed explanations of the functionalities of each segment. Additionally, the extra machine learning portion was done well with much detail, earning extra points. Overall, the work was done with good completion and details.

Final: 1.9/2

Harkirat47 commented 2 months ago

Grading:

Collections - Total 3 / 3, Grade 0.98/1

Had all the requirements but the code is structured in a way that is very incomprihensible to the common person

Lists and Dictionaries - Total 3/3, Grade 0.9888888888/1

To confer upon him a rating of 1/1 would suggest a state of perfection akin to claiming one has exhausted all potential avenues for improvement—an assertion as plausible as suggesting one has reached the end of a bottomless well. The realm of lists and dictionaries offers an endless array of possibilities, each beckoning for exploration and enhancement. Let us not confine ourselves to a finite assessment, but rather, let us embark on an eternal quest for optimization in this ever-expanding landscape of data structures.

APIs and JSON - Total 7/7, Grade .96/1

Could've explained more postman and how postman is calling the / create endpoint and how that endpooint creats a song.

Frontend - Total 8/8, Grade .98/1

The Frontend is perfect with visible attention to detail. It really looks like spotify. When I look at it, It is super hard to tell the difference to the point where he even added the scroll making it look fluid. He explains this in a very reavealing image.

Optional/Extra, ML Algorithm Analysis - Total 5/5, Grade 1/1

The presentation flawlessly navigated the terrain of machine learning, bolstered by insightful screanshot and meticulously commented code. Of particular note was the accessibility of the explanation regarding decision trees, which managed to make complex concepts easily understandable for non-ML professionals.

3.91/4 Regular

1/1 Extra ML