My eportfolio from the course : https://eportfolio.mygreatlearning.com/joshua-julian
I took this course from January to April of 2024. There was three projects along side of weekly tests and optional projects. Projects had two options, low code where most of the code was written for you or full code where you needed to write near 100% of the code from scratch. I chose the full code version for all.
Each project has the ipynb uploaded along with an .html version of it.
The documents posted are the submitted assignments before given feedback by the educators, mentors and professors.
Purpose of the project is to ensure understanding of Python and Data Analysis. We analyzed the data from a food delivery platform. The focus is exploratory data analysis and use of python libraries pandas, numpy, matplotlib and seaborn.
Build a linear regression model for the infamous 1970 Boston Housing data set. The focus of this project is exploratory data aAnalysis, data preprocessing, linear regression model building, testing the assumptions of linear regression model and model performance evaluation.
Utilizing multiple regression models, including linear regression and tree based models and reccomend one to use for resale prediction. Presentation along with Full Code for final turn in. Focus for this project is full implementation from receiving the initial data set to reccommending a model through notebook and presentation. Included presentation.