PORTFOLIO
PROJECT 1: STUDENTS PERFORMANCE IN EXAMS
January 2022
The goal of this project is to discuss the steps taken to find the data set and to tell a story around the acquired data and make visualizations. Therefore, the problem I will be trying to understand is the students' performance in exams and their characteristics. I will be answering questions like:
Does gender play a role in students' exam performance?
What is the performance gap between those who prepared for the exam and who didn’t?
Does the level of parental education level have relations with students' exam performance
PROJECT 2: HIGHER EDUCATION STUDENTS PERFORMANCE EVALUATION
February 2022
The goal of this project is to predict student performance(passing/failing grade) by the end of a semester through some modeling techniques. In this project, I will be doing a machine learning prediction analysis. I will try to find out which factor really affects students' performance and if the factors can be used for prediction. I will be exploring questions like:
Can we predict the students' grade based on certain features?
Which feature is the best to classify students as a pass/fail student?
PROJECT 3:Â HOUSING PRICE PREDICTION
March 2022
Anyone who wants to own a house at some point would want to know the cost of a house. For this project, I will build a model to predict the housing prices using a kaggle dataset for houses in Ames, Iowa. The dataset I will be working with was compiled by Dean De Cock for the sole purpose of data science education. It contains 81 features unlike the Boston Housing Dataset which has 14 features to work with regression.
PROJECT 4: WINE CLUSTERING
April 2022
The goal for this project is to get some experience working with clustering.  I will try to explain what clustering is and how it works. I will also explain the 2 types of clustering I will demonstrate for the project. Therefore I will be working with a wine dataset. I am going to cluster the wine into two groups based on the strength of alcohol.