Slide deck for Word predictor app built for Data Science capstone project.

Building and exploring initial N-gram models for given dataset after cleaning and tokenizing them.

A presentation for my shiny app, which is a COVID19 case tracker - https://akshatt.shinyapps.io/covidcases/

The main goal of the project is to predict the manner in which 6 participants performed some exercise as described below. This is the “classe” variable in the training set. The machine learning algorithm described here is applied to the 20 test cases available in the test data.

Studying the relation between mpg and transmission type and how different variables contribute to the variance between that relation. Single and Multivariate models are generated and analysed while keeping the residuals in check.

The report includes studying the ToothGrowth data from the R package datasets. Post studying, perform a basic exploratory analysis. Finally, state any conclusions drawn after performing hypothesis testing.

The report investigates the simulation of an exponential distribution and checks whether it follows the Central Limit Theorem for large number of simulations.

This document is published as part of Coursework for Reproducible Research Course Project - 2 under Data Science Specialization, Coursera. In this project, the storm database was explored for impact of various weather events on public health and economy.