Collections
Lists and Dictionaries
APIs and JSON
Blog Python API code and use of Postman to request and respond with JSON.
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.
Frontend
Blog JavaScript API fetch code and formatting code to display JSON.
In JavaScript code, 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 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.
In JavaScript code, 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.
Machine learning projects involve significant analysis of algorithms. Consider the steps involved in data preparation and making predictions.
Data Preparation for Analysis:
Demonstrate the process of data cleaning, encoding, and one-hot encoding to prepare data for analysis.
Preparation for Predictions:
Show how algorithms are used to prepare for making predictions.
Understanding Linear Regression:
Discuss the basic concepts and functionality of Linear Regression algorithms.
Understanding Decision Tree Analysis:
Explain the principles and application of Decision Tree algorithms in analysis.