Worldwide-Mortality-Analysis-2021 examines COVID-19's impact on global mortality rates and national responses, revealing significant age-related effects and highlighting disparities linked to institutional trust rather than income inequality.

Data Wrangling and Analysis Project: Analyzing WeRateDogs Twitter Account Data

This is the final community contribution for EDAV Fall 2023, Columbia University. Author: Xinyi Zhao, Jean Law

Proyek Akhir kelas Belajar Analisis Data dengan Python dari Dicoding Indonesia

Analysis tools for machine learning projects

This GitHub repository contains a comprehensive analysis of the popular Iris dataset using various machine learning algorithms, including Logistic Regression, Support Vector Machines (SVM), and Random Forest. Additionally, it explores the impact of different data split ratios (80-10-10 vs. 60-20-20) on model performance.

Explanatory data analysis of anime ratings dataset 🕵🏻‍♀️

This is a part of the exercise project provided by Dicoding in "Learn Data Analytics with Python" course.

This project has two parts that demonstrate the importance and value of data visualization techniques in the data analysis process: Exploratory and Explanatory Data Visualization.

FellowshipAi project

Investigate Ford GoBike Project

Data Analysis of potential factors affecting water pipe breakage

Machine Learning Model on Credit_Score Prediction Including Data Cleaning, EDA, DataPreprocessing, Modeling

EDA analysis and a couple of models from classical machine learning on actual data as of 12.07.2023 about video games. Dataset from kaggle link in readme.

This data set contains 113,937 loans with 81 variables on each loan, including loan amount, borrower rate (or interest rate), current loan status, borrower income, and many others. The analysis explore the factors and patterns in the creditworthiness of borrowers and the borrowing trend of Prosper Loan Business.

Crawl data, process data, visualize, and create ML model for laptop price prediction

This repository demonstrates the use of Pandas Profiling library for Exploratory Data Analysis (EDA) within a Jupyter Notebook. By automating much of the EDA process, the library generates comprehensive and interactive reports, complete with insightful visualizations to facilitate data understanding.

ExcelR_Assignment---Association-Rules---Assignment---9

ExcelR_Assignment---Clustering---Assignment---7

Using linear regression to explain housing prices in Brooklyn, NY from 2016-2020 and estimate how prices changed from quarter 3 and quarter 4 of 2020