List of Events

Here is a list of event, includes speaker session and other intermediate slots (e.g. lunch):

R for Exploratory Data Analysis

R is my favourite language for doing exploratory data analysis. In this talk, I will discuss the use of tidyverse to explore the data. Although, I have mostly used Python to build machine learning models, the ease of use of packages like dplyr and ggplot2 in R allows me to explore the data at high speed and therefore R remains my favourite for exploratory data analysis.

R Short Talk: Interpretable machine learning model, example of using gradient boosted GAM in R

Interpretability is an oft-overlooked yet sometimes critical aspect in machine learning. It allows you to gain more insights about the underlying data generating process and more importantly increase the credibility of your model. A well-developed package in R allows you to build interpretable models with customized complexity in a few lines of code.