univariate-analysis

A New Interactive Approach to Learning Data Analysis

This contains the Jupyter Notebook and the Dataset for the mentioned Classification Predictive Modeling Project

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

Time Series Analysis of Air Pollutants(PM2.5) using LSTM model

Udacity Data Analyst Nanodegree - Project V

Classifying clinically actionable genetic mutations; NIPS-2017 Competition

Auto-Forecasting is a web application that takes in an excel file with univariate time series data and provides forecasts. Auto-Forecasting works on SARIMA modeling.

Time Series Forecasting - Workshop Material @ GIDS-2020

Descriptive Statistics 2020

This case study aims to identify patterns which indicate if a client has difficulty paying their instalments which may be used for taking actions such as denying the loan, reducing the amount of loan, lending (to risky applicants) at a higher interest rate, etc. This will ensure that the consumers capable of repaying the loan are not rejected. Identification of such applicants using EDA is the aim of this case study.

Deep Neural Network for Weather Time Series Forecasting

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

EDA analysis to find insights using R

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

Exploration of the potential customers of insurance. Also, drawing insights with the help of univariate and multi-variate analysis

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.

Predictive modeling

A presentation of my exploratory data visualization results with univariate, bivariate, and multivariate features.

Classifying customers using Logistic Regression

[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).

making analysis using Exploratory and Explanatory visualizations through Univariate, Bivariate, Multivariate Exploration

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

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.

Univariate and multivariate analysis on time series forecasting

Report emphasizing on exploratory and explanatory data visualization techniques used for analyzing FordGoBike bike-sharing system data

1st Project for the Post Graduate Programme in Data Science and Business Analytics at the University of Texas at Austin - Exploratory Data Analysis

A complete Data Visualization tutorial using Seaborn and Matplotlib