Automobile Data Insights: A data analysis project exploring trends in vehicle prices, fuel efficiency, and other key attributes. Uses Python, Pandas, Matplotlib, and Seaborn for data visualization and insights.

A collection of Python libraries for data analysis and visualization, including NumPy, Pandas, Matplotlib, and Seaborn.

This project offers a comprehensive analysis of the Indian startup ecosystem, focusing on key factors such as funding patterns, startup valuations, and regional distribution across India. Using tools like Python, pandas, and matplotli, the project uncovers crucial insights into sectoral dominance, investment trends, and geographical hotspots.

Machine learning project aimed at predicting new COVID-19 cases using historical COVID-19 and mobility data. The project involves data fetching, migration, preprocessing, exploratory data analysis (EDA), feature engineering, data splitting, model training, and evaluation.

Script to graph input latency data

This is a practice Repository consisting of all the notebooks I have practiced to learn python for data science from basics to Advance.

The project focuses on Identification of various Gemstone. The dataset consists of 87 classes.It shows the whole progress and model used to achieve final accuracy. You will gain knowledge of Computer Vision, The model used are CNN(Convolutional Neural Network), MobileNetV2 and VGGNet,The final model used was transfer learning with model MobileNetV2

This repository contains some of the selected data-science projects. https://arunp77.github.io/portfolio-details.html

Seaborn is a visualization library for Python that builds on matplotlib and pandas. It provides beautiful default styles and color palettes for different types of plots, such as histograms, distributions, regression, and matrix plots.

An educational repository intended for First Year Students of VJTI, Mumbai to learn and familiarise themselves with Python, explore it's amazing reach in various domains and also work with making Pull Requests and solving Issues on Github, to experience open source professionally and practically.

This project involves dividing customers into different clusters based on various factors such as salary, marital status, number of kids, education, and other factors using k MEANS clustering

Analyzing the customer dataset and developing a machine learning solution to segment customers into meaningful groups based on their purchasing behavior, demographics, and interaction with past marketing campaigns.

End-to-End Exploratory Data Analysis (EDA) on supermarket sales data using Python, Pandas, matplotlib,seaborn,jupyter and postgresql,pgadmin

Objective: To reduce customer attrition and identify at-risk users for a telecommunications company by building a predictive machine learning model.

Healthcare Data Analysis Project using Python & Power BI. I've extracted impactful insights on Patents & Exclusivities granted by the US FDA to drug products.

Использование библиотек: Matplotlib, Seaborn и Plotly

python code for extracting data from csv file , using Matlab plot and seaborn Libraries

Analiza tendencias musicales mediante técnicas de preprocesamiento, exploración y visualización de datos, utilizando herramientas de ciencia de datos.

This project analyzes customer churn in a telecom company using Python, Pandas, SQL, and data visualization. It identifies key factors like contract type, payment method, and tenure to provide insights for improving retention. The skills gained are applicable in customer retention, user behavior analysis, fraud detection, and HR analytics.

A dedicated repository for learning Seaborn — the statistical visualization library of Python. This is my personal lab where I practice styling, theme control, distribution analysis, relational plots, and advanced visualization techniques.

Projects I've created using Python.

Data visualization in Python with matplotlib and seaborn packages.

Pokemon Exploratory Data Analysis

Analyzed Airbnb's impact on NYC rentals using Python, SQL, and Tableau. Built an ETL pipeline, performed forecasting with scikit-learn, and created interactive dashboards to visualize pricing trends and listing saturation.

Breast Cancer Detection - This project tackles the crucial challenge of early breast cancer detection using machine learning techniques. Using Machine learnig algorithms, Support Vector Machine, Randon Forest.

서울시 열린데이터광장 지하철 23년 9월 승하차 데이터

End-to-end analysis of loan default risk with data cleaning, EDA, visualizations, and ML-based prediction.

Repositório reservado para uma análise de como as industrias brasileiras se encontravam no ano de 2022

🕵️‍♂️🛡️Health insurance claim fraud detection project using machine learning models such as Random Forest, Logistic Regression, and XGBoost, featuring real-time prediction, model comparison, and an interactive Streamlit interface for detecting fraudulent transactions."

Shein, a clothing brand, is using data analytics to design its strategy for 2024. The purpose of this analysis is to help the company enhance customer experience and grow market share focusing on increasing revenue and profitability by understanding consumer trends.