Gurbop
commented
2 months ago .94/1 Lincoln completed all aspects of the review showing understanding in using different methods like post and. He shows how api data requests are used throughout the CPT project. Aditionally he completes extras explaining linear regression and decision tree models showing understanding in machine learning.
From VSCode using SQLite3 Editor, show your unique collection/table in database, display rows and columns in the table of the SQLite database.:
From VSCode model, show your unique code that was created to initialize table and create test data:
In VSCode using Debugger, show a list as extracted from database as Python objects:
In VSCode use Debugger and list, show two distinct example examples of dictionaries, show Keys/Values using debugger:
In VSCode, show Python API code definition for request and response using GET, POST, UPDATE methods. Discuss algorithmic condition used to direct request to appropriate Python method based on request method:
In VSCode, show algorithmic conditions used to validate data on a POST condition:
In Postman, 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 Chrome inspect, show response of JSON objects from fetch of GET, POST, and UPDATE methods:
In the Chrome browser, show a demo (GET) of obtaining an Array of JSON objects that are formatted into the browsers screen:
In the Chrome browser, 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:
Linear regression is a way to predict a value based on the relationship between two variables. It involves drawing a straight line through data points on a graph to best represent how one variable affects another. For instance, it can help predict sales based on advertising spend. The line's position and slope are calculated to show the relationship as accurately as possible.
A decision tree is a model used to make decisions by mapping out different choices and their possible outcomes, much like a flowchart. It starts with a question or decision at the top and branches out into possible responses or further questions, leading to final decisions or actions. This method is commonly used in both business for strategic planning and in data science for predicting outcomes based on input data.