Data science is an inter-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge from structured and unstructured data. Data scientists perform data analysis and preparation, and their findings inform high-level decisions in many organizations.
This documentation is like a quick snapshot of my project in the data field, showing off my skills and know-how in this area.
IIT Ropar – Diginique Techlabs: Python Crash Course in Data Science, Machine Learning, and Artificial Intelligence.
A pipeline to scrape, extract, and analyze book data from web pages to insights.
A Heart Attack Risk Prediction Project
Exploratory data analysis of NCRB Crime in India 2020 dataset using Python, Pandas, Seaborn, and Matplotlib. Covers data cleaning, visualization, and statistical insights.
Random forest analysis of match statistics and team performances in five seasons of the English Premier League (EPL)
The welcome content for the Halerium platform
We solve a regression problem in which it consists of calculating the health insurance charge in the United States Where we will break down the project into 5 phases: Exploratory Analysis. Feature Engineering. Selection of the ideal model. Development of the final model. Creation of a web application in streamlit.
Master's Final Degree Project on Artificial Intelligence and Big Data
This project focuses on detecting fraudulent payment transactions using machine learning techniques.
This is a Loan Approval Prediction Web App built with FastAPI (Backend) and HTML, CSS, JavaScript (Frontend). It predicts whether a loan application will be approved or not approved based on user input.
This is a machine learning web application built with Flask that predicts house prices in Lahore. It uses an XGBoost model trained on custom data and a clean frontend with HTML, CSS, and JavaScript.
This project is a Streamlit-based interactive web application that allows users to explore 128 years of Olympic history (1896–2024) using data analysis and visualizations.
This is a Movie Recommendation System that suggests movies to users based on their preferences. The system uses machine learning techniques to recommend similar movies.
The project is to recognize fraudulent credit transactions. You only need to put the dataset and model will detect the fraudulent credit transactions.
Using exploratory data analysis and k-means clustering to analyze competitive balance in soccer/football
A machine-learning model predicting crypto price from the time-series data
A simple and intuitive web application that predicts house prices based on user input (location, total square feet, number of bathrooms, and number of bedrooms). This app is built using Flask on the backend and a trained Linear Regression model pipeline using scikit-learn.
GLM with sklearn, joblib and SHAP project
A menu-driven Student Result Analysis system built with Streamlit and Pandas. Perform automated grading, topper identification, and subject-wise performance analysis from CSV data.