will-w-cheng / student-public

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Data Structures | CompSci Blogs #5

Open utterances-bot opened 2 months ago

utterances-bot commented 2 months ago

Data Structures | CompSci Blogs

My writeup for the data structures project (Enjoy!)

https://will-w-cheng.github.io/student-public/2024/04/16/Data-Structures-Blog_IPYNB2.html

Harkirat47 commented 2 months ago

1.93/2

Insightfull blog, Very good usage of the model file, see a lot of thought in the Datbase handling. Frontend thumbnails match the style greatly, EVERYTHING WORKS, Might recomend more videos to make it look more complete. looks fully complete. Everything is exceptional with insightful writing

will-w-cheng commented 2 months ago

test

AaronH1234 commented 2 months ago

Reviewer: Aaron Hsu 1.92/2

This is a great blog, meet every requirement that was given. Provide good model and styling. Detaily description under every picture. One thing to improve is to add more test data to the videos so it doesn't look empty. Overall, it's a great writeup.

YeongsuKimm commented 2 months ago

Includes Searching, Sorting, Hashing / Dictionaries, Algorithms, Object-Oriented design, Collections / Lists (6) PBL Project Requirements

Total Points 4/ 4 Extra Points 0.8 / 1 Collections - Total 3 / 3 , Grade = 0.95/1

Blog Python Model code and SQLite Database.
    Show your unique collection/table in database, display rows and columns in the table of the SQLite database from VSCode using SQLite3 Editor.
    Show your unique code that was created to initialize table and create test data from VSCode model.

Lists and Dictionaries - Total 3/3 , Grade = 0.97/1

Blog Python API code and use of List and Dictionaries.
    Show a list as extracted from database as Python objects in VSCode using Debugger.
    Show two distinct examples of dictionaries, show Keys/Values using debugger in VSCode.

APIs and JSON - Total 7/7 , Grade = 0.98/1

Blog Python API code and use of Postman to request and respond with JSON.
    Show Python API code definition for request and response using GET, POST, UPDATE methods in VSCode. Discuss algorithmic condition used to direct request to appropriate Python method based on request method.
    Show algorithmic conditions used to validate data on a POST condition in VSCode.
    Show URL request and Body requirements for GET, POST, and UPDATE methods in Postman.
    Show the JSON response data for 200 success conditions on GET, POST, and UPDATE methods in Postman.
    Show the JSON response for error for 400 when missing body on a POST request in Postman.
    Show the JSON response for error for 404 when providing an unknown user ID to a UPDATE request in Postman.

Frontend - Total 8/8 , Grade = 0.97/1

Blog JavaScript API fetch code and formatting code to display JSON.
    Show response of JSON objects from fetch of GET, POST, and UPDATE methods in Chrome inspect.
    Show a demo (GET) of obtaining an Array of JSON objects that are formatted into the browsers screen in the Chrome browser.
        Describe fetch and method that obtained the Array of JSON objects in JavaScript code.
        Show code that performs iteration and formatting of data into HTML in JavaScript code.
    Show a demo (POST or UPDATE) gathering and sending input and receiving a response that show update. Repeat this demo showing both success and failure in the Chrome browser.
        Show and describe code that handles success. Describe how code shows success to the user in the Chrome Browser screen in JavaScript code.
        Show and describe code that handles failure. Describe how the code shows failure to the user in the Chrome Browser screen in JavaScript code.

Optional/Extra, ML Algorithm Analysis - Total 5/5 , Grade = 0.95/1

Machine Learning Algorithm Analysis

Show algorithms and preparation of data for analysis. This includes cleaning, encoding, and one-hot encoding.
Show algorithms and preparation for predictions.
Discuss concepts and understanding of Linear Regression algorithms.
Discuss concepts and understanding of Decision Tree analysis algorithms.

Has everything required with thorough explanations on each. Well-organized and easy to follow. Lacking a bit in the machine learning segment. Overall, well done.

Total Average = 0.95+0.97+0.98+0.97+0.95 = 4.80 4.80/5 = 96%