There are 1 repository under metplotlib topic.
Olympics Data Analysis Web Application using Streamlit. For development, I will be using Python and Pandas. For plotting, I will be using Seaborn and Plotly libraries.
The "kidney-stones-Detector" is an advanced system delivering precise detection and classification of kidney conditions including stones, cysts, tumors, and normal states from medical imaging data. With an impressive accuracy of 98.87%, this machine learning-powered models offer reliable insights for medical professionals.
Learning Python For Data Engineering
This is a sophisticated app designed to analyze financial datasets and uncover market trends. Leveraging powerful tools like Python, Pandas, and Scikit-learn, this app offers deep insights into stock performance, helping investors and analysts make informed decisions. Explore data-driven strategies and stay ahead in the financial market.
Exploratory data analysis of food order trends using Python and Jupyter Notebook.
A Machine Learning Project that predicts student grade and performance from a Dataset. Copule of Libraries are used for data pre-processing, training model, heatmaps, trees and other Algorithms.
Prediction model for profit of 50 startups dataset by Multiple Linear Regression
Bangalore House Price Prediction by KNN
Data Analysis of Bank by Logistic Regression.
Company Data Analysis by Random Forest.
Crime Data Analysis by Clustering.
Prediction model for Delivery Time by Simple Linear Regression
East West Airlines Analysis by Clustering.
This project is developed on python language, It scraps the data from a famous website BBC/Urdu and stores it in an CSV file. There are also other methods through them we read the csv file and manuplate its data
Linea De Enfasis Ciencia de Datos y Machine Learning
Diwali-Sales-Analysis-Project
This project explores loan data to identify trends and insights that can help in understanding lending patterns, borrower behavior, and risk factors. By using Python and Jupyter Notebook, the project analyzes factors like borrower demographics, credit scores, loan purposes, and default rates to create a detailed view of loan performance.
The IPL Data Analysis project focuses on extracting valuable insights from IPL match data using various data analytics techniques. By analyzing historical match outcomes, player performances, team comparisons, and venue statistics, the project visualizes trends and patterns through graphs like bar charts, line graphs, and scatter plots.
Fraud Check Analysis by Random Forest.
Health Analysis Report based on money spent on health and its impact on life expectancy.
Prediction model for Insurance Cost dataset by Regression
Data Analysis of iPhone Purchase Records by Decision Tree.
Data Analysis of iPhone Purchase Records by KNN.
A Capstone Project on Makaan Property Analysis by Machine Learning.
Prediction model for Salary Hike by Simple Linear Regression
Predict salary of new employee by Polynomial Regression.
Prediction model for price prediction by Multiple Linear Regression
Travel Data Analysis by ARIMA.
A case study on Weather Analysis during World War 2 by Machine Learning.
Projeto Challenge TelecomX-BR - Formação Data Science do programa ONE - Oracle Next Education em parceria com a Alura.
A comprehensive exploratory data analysis (EDA) project on Zomato’s restaurant dataset to uncover key insights about restaurant trends, locations, cuisines, ratings, and pricing. This project demonstrates the use of Python libraries for cleaning, visualizing, and interpreting real-world food industry data.
Analyze netflix data to uncover insights about movie genres, ratings, release trends, and availability by country.
This project uses machine learning algorithms to predict earthquake damage based on historical data. It analyzes factors like magnitude, depth, and location to estimate the potential damage caused by earthquakes.