An Introduction to XGBoost R package
The GBM (boosted trees) has been around for really a while, and there are a lot of materials on the topic. This tutorial tries to explain boosted trees in a self-contained and principled way using the elements of supervised learning. We think this explanation is cleaner, more formal, and motivates the variant used in xgboost.
How to create animated GIF images for data visualization using gganimate (in R)?
This article will tell one of the ways to do so using animated GIF images (Graphics Interchangeable format). This would be particularly helpful when you want to show time / flow based stories.
BallR: Interactive NBA Shot Charts with R and Shiny
This example is about building a tool called BallR, using R Shiny framework, to explore NBA shot data at the player-level. It calculates aggregate statistics like field goal percentage and points per shot attempt, and compares the selected player to league averages at different areas of the court.
Practical guide to implement machine learning with CARET package in R
This post is about Caret package for solve almost any supervised machine learning problem. It provides a uniform interface to several machine learning algorithms and standardizes various other tasks such as Data splitting, Pre-processing, Feature selection, Variable importance estimation, etc.
Intro to The data.table Package
Its a helpful document to understand data.table package that provides working with large data sets, also can behave just like a data frame. Data.table package offers fast subset, grouping, update, and joins.