An interactive scatterplot visualization.
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Updated
Jan 27, 2017 - Processing
An interactive scatterplot visualization.
Estimating tip% for the noble souls that get pizza for you!
In this project, the task is to build a sentiment classifier, which will detect how positive or negative each tweet is. We will create a csv file, which contains columns for the Number of Retweets, Number of Replies, Positive Score (which is how many happy words are in the tweet), Negative Score (which is how many angry words are in the tweet), …
D3.js-based Interactive Visualization Comparing 2014 ACS 1-year Estimates (US Census Bureau & CDC) of Obesity, Smoking, and Lack of Healthcare Rates in Each State to Poverty Rates, Median Age, and Median Household Income
Investigating a 2014 demographics dataset to create interactive visualizations
This is a collection of Python scripts that I have written while learning how to code. These scripts are used for graphing in Python, using libraries such as Seaborn, Matplotlib, and Numpy.
This repository you are browsing contains intermediate level piece of codes which are useful for cleaning, exploratory analysis, handling of missing data points, outlier detection and different visualization techniques using graphics, ggplot2, tidycharts, ggExtra packages. Also in particular part of the script you can get basic information about…
[Personal Project] - Project:- custom-charts-clone, Built with love
Analyzed cryptocurrencies data using unsupervised machine learning model, PCA, K-means and visualized with 3D and scatter plot.
This python code shows howw regression is handled in case of categorical variables using duumies. It calculates the multiple regression code and shows the regression table. It also performs the residual analysis.
Plotting of the Confidence interval and Prediction interval for a Linear Regression model.
Data visualization - qualitative & quantitative data (Airbnb listings for NY)
This project aims to do the detailed analysis of World happiness index using Python and create a dashboard summarizing entire analysis using both Tableau and Plotly Dash.
AIND Jupyter Notebook to predict student admissions using Keras Neural Networks
Simple plotting library for Haskell
A tool for visualizing local elections with more than 2 viable candidates
GlassDoor Machine Learning Challange to predict which users would press submit button on basis of features given.
Used unsupervised machine learning, PCA algorithm, and K-Means clustering to analyze and classify a cryptocurrency database.
The purpose of this study was to compare the performance of Pymaceuticals’ drug 💊of interest, Capomulin, against the other treatment regimens.🐭
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