Here is a list of event, includes speaker session and other intermediate slots (e.g. lunch):
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.
Language: Cantonese (Slides: English)
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.
How R can be deployed across business operations to make an impact and how it can be seamlessly integrated with the latest AI framework to equip the business with state of art AI fire power.