A curated collection of AI, data engineering, and DevOps projects featuring real-world applications, advanced techniques, and tutorials—ideal for learners and practitioners exploring data science and machine learning.

An open-source Python library for Data Scientists & Data Analysts designed to simplify the exploratory data analysis process. Using Edvart, you can explore data sets and generate reports with minimal coding.

Exploratory data analysis of Airbnb bookings in New York City to gain insights into the travel industries and Uncovers trends, patterns, user preferences and behavior. Utilizes Python libraries for data exploration, data cleaning, manipulation, and visualization. Provides valuable insights for travelers, hosts, and the Airbnb business.

This data project on Python uncovers and visualizes untapped patterns regarding all Nobel Prize laureates up to date.

Building And Deploying A Netflix Recommender System On Heruko

# Women's E-Commerce Clothing Reviews Data Analysis

Abstractive summarization of Reddit datasets with Transformers.

Built an interactive Tableau dashboard to analyze Airbnb data and developed a Streamlit application for trend analysis, pattern recognition, and data insights using EDA. Explored variations in price, location, property type, and seasons with interactive plots and charts, greatly aiding decision-making in the hospitality and real estate industries.

This repository contains a Jupyter Notebook demonstrating a practical example of data science and machine learning for heart disease classification.

Pandas practice notebooks for data analysis.

NYC health is one of the well-known centers in New York City to offer PCR tests for COVID-19 the center decided to establish ten mini examination centers in MTA stations. Thus NYC health is now in a mission to find the most crowded stations in New York City based on analyzing the MTA stations dataset which will give a better understanding of the…

Performed feature engineering and data cleaning on text data using lemmatization techniques and stop word removals.

A ML application focused on EDA and basketball analytics, showcasing data visualization and insights using Python and relevant libraries.

This project offers an Exploratory Data Analysis (EDA) on company stakeholders, including management, employees, shareholders, and others. Conducted in Python via Google Colab, it covers data transformation, clustering, statistical analysis, PCA, and predictive modeling. Visualizations provide insights into stakeholder roles and influence.

Determine the breed of a dog in an image

🚗 Built an interactive Automobile Sales Dashboard using Python & Plotly Dash. Features dynamic filters, multi-chart views, and KPIs to analyze sales by year, region, and vehicle type. Demonstrates data wrangling, visualization, and dashboarding skills for business insights.

Successfully developed a resume classification model which can accurately classify the resume of any person into its corresponding job with a tremendously high accuracy of more than 99%.

End-to-end healthcare ML workflow featuring data ingestion, DQA procedures, feature engineering, RandomForest modeling, and accuracy/recall optimization. Designed to simulate a production-ready analytics pipeline supporting clinical decision-making.