seborn

Linear regression house-price predictor with scikit-learn (EDA → encoding → train/test → metrics).

Contains code and documentation for conducting Exploratory Data Analysis (EDA) on various datasets. The EDA process involves examining and visualizing datasets to better understand their characteristics, relationships, and insights that can be derived from them.

🤖 Whatsapp-Chat analysis This project provides an interactive dashboard to analyze WhatsApp chat data.

Web application for detecting fraudulent credit card transactions using machine learning

Machine Learning -----> Supervised Learning , Unsupervised Learning

Deep Learning ---- ANN, CNN, RNN, LSTM Algorithm

🤖 Streamlit App Spam Emails Classification Project Deep Learning 🔥

🤖NLP, Deep Learning, Machine Learning

A machine learning-based web application for predicting cancer risk based on various health and lifestyle factors.

🐍 Big Data Analysis on Python / Jupyter Notebook / Colab

Welcome to SafeVault Analytics! This project isn't just about code; it's about solving a real-world dilemma: How do we use data to save lives without spying on people? In 2026, data privacy is a human right. But for researchers studying conditions like PCOD, privacy laws often mean they can't get the data they need to build helpful AI.

Construction d’un pipeline PySpark pour l’analyse des performances footballistiques saison par saison, avec calcul de KPI, ranking des équipes et stockage optimisé en Parquet partitionné.

"Exploratory Data Analysis (EDA) scripts and resources for uncovering insights from datasets. Includes data cleaning, visualization, statistical summaries, and correlation analysis using Python libraries like pandas, matplotlib, and seaborn."

This project analyzes EV sales data across Indian states, focusing on sales distribution by vehicle type, category, and region.

🐍 A/B Test on on Python / Jupyter Notebook / Colab

A Python Tkinter-based data visualization tool that converts CSV data into interactive charts using Pandas, Seaborn, and Matplotlib enabling no-code data analysis.

Analyzed traffic accident data to identify patterns related to road conditions, weather, and time of day. Visualized accident hotspots using heatmaps and bar plots.

Interactive sales dashboard built with Streamlit & PostgreSQL to analyze Superstore KPIs, regional performance, and product trends.