Presentation slides for the Data Science Capstone Project - a NLP ngrams text predictor application.

This is the first milestone report for the Data Science Capstone Project

Overview of the background of the data, application, and it's functionality.

Assignment for Developing Data Products to test out creating web presentation slides and using PLOTLY package.

This is the course project for the Practical Machine Learning Course on Coursera. Data for this project came from the Human Activity Recognition project from Groupware@LES. In this project, we will use data from accelerometers on the belt, forearm, arm, and dumbell of 6 participants to predict the manner in which they did the exercise. This is the “classe” variable in the training set. We train 4 models: **Decision Tree**, **Random Forest**, **Gradient Boosted Trees**, **Support Vector Machine** using k-folds cross validation on the training set. We then predict using a validation set randomly selected from the training csv data to obtain the **accuracy** and **out of sample error rate**. Based on those numbers, we decide on the best model, and use it to predict 20 cases using the test csv set.

This is part two of the final project for Statistical Inference course on Coursera. This course is part of the Data Science Specialization Track on Coursera offered by John Hopkins.

This is part one of the final project for the statistical inference course offered by John Hopkins through Coursera. This course is part of the Data Science Specialization Track on Coursera.

Final project for the Coursera course: Reproducible Research. This is course 5 of 10 of the Data Science Specialization Track offered by John Hopkins.