Speed Up Exploratory Data Analysis (EDA)

Jared Kushner and his partners used a program meant for job-starved areas to build a luxury skyscraper

Components for interactive scientific writing, reactive documents and explorable explanations.

Pre-Modelling Analysis of the data, by doing various exploratory data analysis and Statistical Test.

A 60 days+ streak of daily learning of ML/DL/Maths concepts through projects

Predicting demand of Taxi in a given area and location of New York City.

Python Package for Quick Exploratory Data Analysis

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

Open-Sourced Data Science project, that is made on the basis of a data-set from Kaggle.com. This data-set provides data about the Green House Gas Emission in some countries from 1990-2017.

A case study on MPG dataset.

Kaggle Projects Prediction and Real World Projects

Real-time, interactive exploration of 3D image stacks

Exploratory data analysis on datasets available on Kaggle - https://www.kaggle.com/

Class project for Data 601 @ UMBC - Data characterization projects using Python Sci-Kit Learn

This is notebook where I just create random idenitity and Autoencoder networks to actually see what the convolution layers are learning. Mostly I visualise the internal layers activation and conclusions can be drawn about what the hidden layers are learning. For anyone who is trying to build CNN. This can also help them guide them into thinking and creating proper hidden representation.

Demo on performing exploratory data analysis (EDA) on train service disruptions based on scrapped (user generated contents) tweets from the train operator's (SMRT) twitter account

Tariff is a list of expenses that incur while transporting the goods from one distance to another distance. Tariff is also dependent on seasonal and non-seasonal factors also. This project is aimed at predicting the tariff ratesfor truck load by using the different machine learning algorithms like lasso regression, elastic net regression, ridge regression and linear regression. Tariffisa combination of lot ofthings and tariff rate is dependent on some ofthe factorslikeYear, Road, SeasonalImpact, Fuel Cost,Distance, Weight, Toll charge, Demand, labour cost, travel expenses etc. Using some ofthese factors and by employing the above-mentioned machine learning regression algorithms we will be trying to predict the tariff rates on the trucks. By doing this we can help the industriesto estimate the tariffratesso that they can take the necessary actions and they can make their business run inprofitable way. This model helps small- and large-scale firms to control and manage the cost on transport.

an analysis of crime in a given area

Visualizing and Analysis of Instagram direct conversations

Big Data Implementations - Quantitative_Research

Data Science Capstone : Machine Learning applied to FCC Net Neutrality comments

Udacity Data Analyst Nano Degree Program Capstone Projects

A desktop application was created which will allow user to perform basic data analysis and pre-processing of CSV dataset easily.

Exploratory Data Analysis

As part of this project, we have used Regression Analysis on top of a panel data on Guns in USA to determine the "Effect of Shall-Carry Law on Violence Rate and Incarceration Rate in United States".

Predicting whether the consumer has purchased the item through social media advertisement based on its age and estimated income.

Exploratory Data Analysis on the Coronavirus data set available in South Korea and Time Series Forecasting using Facebook's Prophet

An interactive astrophysics project, exploring the masses of dead stellar objects (black holes and neutron stars). I used d3.js, a touch of jquery, flowtype, and advanced SVG techniques (in vanilla javascript) for this project.

This project is to analyze data on the quality of redwine . I have used R to do EDA on the data.