Mehak0310/Credit-EDA-Case-Study

Perform Exploratory Data Analysis(EDA) on loan applications to understand how various client attributes (like marital status, education, occupation, etc.) influence the tendency of default.

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renatokano/cn-pulsar-star-challenge

[Codenation] Explore the main functions of probability distributions such as PDF, CDF and quantiles, and the relationships between normal and binomial distributions. We will also explore the 'Pulsar Star' data set provided by Dr. Robert Lyon (University of Manchester).

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Usama-Tariq/Udacity_Communicat-Data-Findings_Project-5_DAND

Performed an exploratory data analysis using python and presented explanatory plots that convey insights of data.

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Defcon27/Data-Analysis-of-Indian-Automobile-dataset-using-Machine-Learning-in-R

The project aims to perform various visualizations and provide various insights from the considered Indian automobile dataset by performing data analysis that utilizing machine learning algorithms in R programming language.

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Samirnunes/eda_sql_univariate_tech_layoffs

Análise Univariada em SQL: o objetivo deste projeto é utilizar os dados atuais acerca das demissões nas áreas de tecnologia de várias empresas para praticar o uso da linguagem SQL (Standard Query Language) para análise de dados.

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manishkr1754/Loan_Eligibility_Prediction_Python

Predict Loan Eligibility for a Finance company

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shreyas-singhal/Lead-Scoring-Case-Study

X Education Organization wants to identify if a customer registered on their website for enquiry is a potential customer or not. Using past data to build a machine learning algorithm

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Maruthi18/World-Economic-Indicator-Data-analysis

How Country's GDP/Capita depends

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hajarmerbouh/Heart-Disease-Prediction

Application web R Shiny : Heart Disease Prediction

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nasr-edine/univariate_analysis_python

Univariate Data Analysis in Python about Tree Distribution in Paris

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nitishkthakur/selfplot

A python package with standard data visualization functions with reasonable defaults for use in Exploratory Data Analysis and Model Diagnostics.

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pradeepdev-1995/Feature-Selection-Techniques

Feature selection techniques in machine learning is a process of automatically or manually selecting the subset of most appropriate and relevant features to be used in model building. Here we are taking a machine learning regression problem and shows the different steps in feature selection process

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dorothy-nguyen/prosper-loan-exploration

This project is conducted as a part of Udacity Data Analyst Nanodegree. The purpose of this project is to perform exploratory data analysis, then create a presentation with explanatory charts that conveys findings and insights from the data set provided.

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marcello-calabrese/edatemplates

Exploratory Data Analysis standard templated in markdown and txt format

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darshil2848/Bike-Shraing-Demand-Prediction

Booming Bike Sharing Analysis and Demand Prediction

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MoinDalvs/Learn_Visualization_on_Matplotlib

Matplotlib The Figure is the overall window or page that everything is drawn on. It’s the top-level component of all. To the figure you add Axes. The Axes is the area on which the data is plotted. A figure can have multiple axes. Note: when you see, for example, plt.xlim, you’ll call ax.set_xlim() behind the covers. All methods of an Axes object exist as a function in the pyplot module and vice versa. Mostly, you’ll use the functions of the pyplot module because they’re much cleaner, at least for simple plots!

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sandipanpaul21/EDA-in-Python

Exploratory Data Analysis Theory and Python Code

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kedarghule/Statistical-Analysis-of-Insurance-Claims

This project explores the data of medical insurance claims. Descriptive Analysis, Exploratory data analysis, Univariate, Bivariate and multivariate analysis is performed to explore the data and how different features are correlated to each other. Finally, hypothesis testing is performed by employing t-test, Chi-squared test and One-way ANOVA.

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bushra-ansari/Predicting-Term-Deposit-Subscription-by-a-Client-by-SVM-Classifier

Support Vector Machine Classification model is applied on bank dataset containing 41188 rows and 21 columns. The data is related with direct marketing campaigns of a Portuguese banking institution. The marketing campaigns were based on phone calls. Often, more than one contact to the same client was required, in order to assess if the product (bank term deposit) would be ('yes') or not ('no') subscribed.

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MaheenAnees/Exploratory-Data-Analysis

This repository is created as part of the course Data Science. Have conducted exploratory data analysis on the given dataset using univariate, bivariate as well as multivariate analysis

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darshil2848/Loan-Lending-Club-Case-Study

Loan Lending Club Case Study by Darshil Ajay Parekh

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ash-deol/EDA-Mini-Project

Dataset recording people to invest in each other in a way that is financially and socially rewarding. On loans, borrowers list loan requests between $ 2,000 and $ 35,000, and individual investors invest as little as $ 25 in each loan listing they select. Prosper handles the servicing of the loan on behalf of the matched borrowers and investors. Few more different questions were also included in that mini-project not based on a summary.

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NabilahSharfina/Ruangguru-Bootcamp

Final project program DBA mitra Ruangguru X Studi Independen Bersertifikat Kampus Merdeka batch 2

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ajuRavi/EDA-IPL

About Exploratory Data Analysis on IPL data (2008 - 2020).

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nani757/univariate-analysis_eda

eda

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MIchelAshraf/Ford-Bike-data-set-analysis

Explanatory/Exploratory Data Analysis on Ford-bike data-set

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MIchelAshraf/Telecom-Customer-Churn-dataset-analysis

Explanatory/Exploratory Data Analysis on Telecom-Customer-churn.

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LoneN3rd/Statistical-Data-Analysis

Perform univariate and bivariate analysis to prepare data for modelling in later stages

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chinmayeeguru/Loan-Default-Risk-Analysis

To identify customers who are more likely to default loan repayment

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keenan-cooper/Marketing-Analytics-for-a-Food-Delivery-Platform

Udacity - Data Analyst Nanodegree - Project 5 - Data Visualization

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kshitij-raj/Lending-Club-Analysis

Analysis to understand the driving factors (or driver variables) behind loan default.

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rrchaubey/Statistical-Analysis-on-PIMA-DIABETES

This repo will introduce you end to end use case of Statistics and Machine Learning together.

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Abhishek20182/Communicate-Data-Findings

Udacity Data Analyst Nanodegree - Project V

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abhikumar22/Exploratary-Data-analysis-on-Habermans_Cancer-Survival-DataSet

Here, we are doing to perform exploratory data analysis on haberman survival dataset by applying various techniques like univariate analysis, bivariate analysis etc

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antonietamg/Multi_MagDFA

Multivariate Magnitude Detrended Fluctuation Analysis

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tanish36/Tensorflow-Projects

TensorFlow Projects

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somjit101/Microsoft-Malware-Detection

A multi-class classification problem where the task is to classify a file to one of 9 types of Malware usually found in a Windows system, using information from the raw data and metadata of the file.

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Davidelvis/Telecommunication-Project

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1218muskan/MLnow_2.0

Machine Learning Hands-on

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SmartNamDevoloper/Clustering_Countries

This project demonstrates a Clustering Model using Python. An international humanitarian NGO that is committed to fighting poverty and providing the people of backward countries with basic amenities and relief during the time of disasters and natural calamities. It has been able to raise around $ 10 million. The model is needed to help decide how to use this money strategically and effectively. The significant issues that come while making this decision are mostly related to choosing the countries that are in the direst need of aid. The model is used to categorize the countries using some socio-economic and health factors that determine the overall development of the country.

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ag-ds-bubble/GIDS-2020-Time-Series-Forecasting-Workshop

Time Series Forecasting - Workshop Material @ GIDS-2020

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anushkaparadkar/lending-club-case-study

Case study to identify risky loan applicants and understand factors that contribute to a loan default.

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Develop-Packt/Understanding-and-Describing-Data

This module will cover the role SQL in the world of data. It also introduces you to basic mathematical and graphical techniques to analyze data.

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greghor/tprojection

Visualize the relation between a dependent variable and any feature in a meaningful way

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r1shbh/data_visualization

A complete Data Visualization tutorial using Seaborn and Matplotlib

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Develop-Packt/Interpreting-the-credit-card-defaulter-dataset

Explore data related to credit card defaulters to identify customer personas. Discover patterns in the data and interpret how each feature impacts the target variabl

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Develop-Packt/Identifying-Online-Shoppers-Purchase-Intentions

Perform univariate and bivariate analysis to analyze the behavior of online shoppers. Learn how to implement clustering and make recommendations based on the prediction

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