Data Science Portfolio

This repository contains projects that are completed by myself for self-learning, and hobby purposes. The projects are written in Python (Jupyter Notebook) and R markdown. Click on the project titles to access the codes and writeups.

Please feel free to reach out either by email or LinkedIn, if you are interested in learning more about my skills, experience, and academic background.

Projects

• R

  • Health Data Analysis: In this project I proposed three research questions related to behavioral health risks and tried to find answers through exploratory data analysis.

  • Cricket Data Analysis: I grew up playing cricket and still love playing it. Just wanted to look at a cricket dataset using R and choose my best 11 based on the analysis and my cricketing knowledge.

  • Exploratory Movie Data Analysis: This project is focused on exploratory analysis of a movies dataset by cleaning the dataset, and then exploring relationships between identified variables.

• Python

  • Predicting House Prices: We’ll attempt to predict the median price of houses in a given Boston suburb in the mid-1970s, given data points about the suburb at the time, such as the crime rate, the local property tax rate, and so on.

  • Handwritten Digits Classification: In this micro project we'll try to classify grayscale images of handwritten digits (28 x 28 pixels) into thier 10 categories (0 through 9). We will use the MNIST dataset which has a set of 60,000 training images, and 10,000 test images.

  • Predicting Loan Payback: Investors are often interested in learning the risks involved in lending money. This project attempts to predict the people (borrowers) who have high probability of paying back their loans.

  • Customer Segmentation: This project involves analyzing KPIs and segmenting customers using GMM and K-Means clustering algorithms. The dataset used here is available on Kaggle.

  • Stock Market Analysis: I will explore the stock market data for some tech giants in this project. I am particularly interested in Microsoft's stock.

  • World Trends in Fertility and Life expectancy: In this project, I explore fertility and life expectancy statistics by country through scatterplots. The scatterplots are categorised by countries regions.