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Business & Data Analyst | Data Scientist | Product Analyst 🇮🇳🇮🇳🇮🇳
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Australian-Bank-ATM-Fraud-Detection-using-ML-AutoML
November 3, 2025 – November 3, 2025
Built a Machine Learning model to detect fraudulent ATM transactions for an Australian bank using PyCaret AutoML. Conducted EDA, preprocessing, and model tuning. Tuned QDA achieved 99.3% accuracy and 0.855 recall, ensuring strong fraud detection with stable cross-validation performance.
View ProjectKidney-Disease-Classification-Project
November 3, 2025 – November 3, 2025
This is a classification problem where the goal is to predict whether a patient has chronic kidney disease (CKD) or not. The dataset consists of medical records of 400 patients, collected from reliable healthcare data sources.
View Projectairline-price-prediction-app
November 1, 2025 – November 1, 2025
A modern Streamlit web app for flight price prediction using machine learning
View ProjectContent-Based-Movie-Recommendation-System-Data-Mining
October 28, 2025 – October 28, 2025
A content-based movie recommendation system that suggests similar movies using cosine similarity. It analyzes genres, cast, crew, keywords, and overviews. Includes automated EDA with ydata_profiling and CountVectorizer-based text feature engineering for similarity modeling.
View ProjectTelecom-Churn-Prediction-using-PyCaret-Manual-ML
October 26, 2025 – October 26, 2025
Telecom Customer Churn Prediction using Machine Learning. Built and tuned multiple models (Logistic Regression, Random Forest, XGBoost, SVM, KNN, Naive Bayes, Voting Classifier) manually and compared with PyCaret automation. Focused on feature engineering, hyperparameter tuning, and business-aligned model evaluation.
View ProjectBangalore-House-Price-Prediction_LinearRegression
September 29, 2025 – September 29, 2025
Bangalore House Price Prediction
View ProjectCIFAR-10-Classification-Using-Deep-Neural-Networks-Without-CNN-
April 17, 2025 – April 17, 2025
CIFAR-10 Classification Using Deep Neural Networks (Without *CNN*)
View ProjectCar-Insurance-Claim-Prediction
January 15, 2025 – May 17, 2025
The aim of this project is to predict whether a customer will file a claim on their car insurance policy based on various factors, including policyholder demographics, car details, and policy characteristics. The project involves end-to-end data processing, exploratory data analysis (EDA), feature selection, data balancing, and predictive modeling.
View ProjectCase-Study-1---Danny-s-Diner
November 25, 2024 – November 25, 2024
Case-Study-1---Danny-s-Diner — GitHub repository
View ProjectCultural Fit Analysis
The candidate's portfolio of personal projects demonstrates initiative, self-learning, and a passion for data science. The variety of projects (e.g., recommendation systems, fraud detection, price prediction, medical classification) indicates a broad interest and adaptability, which generally aligns well with a dynamic team environment. The use of tools like PyCaret suggests an openness to leveraging automation and efficient workflows.
Soft Skills & Operational Fit
The provided data does not contain information to assess soft skills or operational fit beyond project descriptions. Project diversity suggests an ability to tackle different problem types.