top of page

Tech Activities

Academic Projects

My projects makes use of vast variety of latest machine learning tools for developing and interpreting models.

World Happiness Analysis | R

  1. Analyzed global happiness data of 155 nations spanning 2015-2019 via R.

  2. Spotlighted Finland’s peak happiness scores and discerned primary contributors using R visuals.

  3. Leveraged R to garner a deeper comprehension of evolving happiness metrics.


Centralized Metallic Company Database 

  1. ​Implemented an ERP module in SQL Workbench that encapsulated sales, purchase, and fiscal sectors.

  2. Bridged SQL with NoSQL MongoDB, ensuring seamless MYSQL and Cypher query compatibility.

  3. Employed Python and Tableau for vivid data visualization and meticulous analysis.

SQL, Python, Tableau

Depression, Stress, and Anxiety Prediction Analysis

  1. Analyzed mental well-being surveys in Python to discover patterns in personality responses.

  2. Predicted depression with a staggering 98.4% accuracy using Logistic Regression in ML.

  3. Undertook extensive data sanitization and employed classification algorithms for penetrative insights.

Python, Machine Learning

Airline Customer Satisfaction Prediction

  1. Cleaned and analyzed a 120K-record dataset, conducted statistical tests, and derived insights.

  2. Implemented KNN, Decision Tree, and Random Forest models with hyperparameter tuning, achieving 95% customer satisfaction prediction accuracy.

  3. Identified key factors impacting customer comfort through data modeling and visualization.

Python, ML, Alteryx, PowerBI
bottom of page
Your Website Title