Hotel Data Analytics

During this project, I delved into the world of data using the powerful Pandas library, analyzing multiple datasets to gain insights into the hotel industry. This Project involved: Exploratory Data Analysis (EDA), Data Cleaning, Data Transformation and Insight Generation.

Sepsis Prediction Classification

Developed predictive models using Gaussian Naive Bayes, Random Forest, and Decision Tree algorithms to identify sepsis risk from clinical data.

Big Data in Computational Finance

Engineered an investment portfolio optimization model using linear programming to maximize expected profits. Implemented Solver for scenario-based strategy analysis, achieving an $11,200 expected profit from a $20,000 investment.

Shipment Price Prediction

Developed regression models employing Linear Regression, K-Nearest Neighbors, Random Forest, AdaBoost, and Decision Tree algorithms to predict shipment costs for logistic companies, performed hyperparameter optimization to identify the best-performing algorithm, and implemented end-to-end project.

Sentimental Analysis of Customers reviews of Amazon Products

This project focuses on sentiment analysis of customer reviews for Amazon products. We utilize NLTK and employ Naive Bayes classifiers (Multinomial NB, Bernoulli NB) and Logistic Regression to classify sentiments. Additionally, we build a simple classifier for Amazon reviews.

Marketing Analytics Business Case

I led a comprehensive marketing analytics project using Power BI, Microsoft SQL Server Express, and Python. The project identified four KPIs and analyzed a conversion rate drop from 11.58% to 8.48%. I processed data from 11.28 million interactions, noting shifts in sentiment and customer reviews.