The R Consortium recently reconnected with Poo “KH” Kuan Hoong, founder of the Malaysia R User Group (Also on Facebook). We talked with KH last year when he spoke about Hosting Malaysia’s Largest Annual R Conference. KH is deep into planning and preparation for this year’s R Conference, the first time it will be held face-to-face in two years! R confeRence 2023 is Malaysia’s largest physical R User Conference. It features Malaysian industry leaders and academicians. The conference will be held at Sunway University on October 28, 2023. Please come and join the Malaysia user group if you are near Subang Jaya, Malaysia. You will learn, explore, and more.
What’s new with the Malaysia R User Group (MyRUG)?
Since our last chat, we’ve expanded our outreach by collaborating with Malaysia R-Ladies. Initially, there was only one R user group in Malaysia. However, we felt the need to support and inspire our female participants. So, we established the R-Ladies chapter for Malaysia.
Our annual R ConfeRence is ongoing. For the past two years, the pandemic forced us to host it online. But this year, we’re thrilled to announce it’ll be a physical event at Sunway University. At the moment, we’re planning for 15 talk sessions, each spanning around 40 to 45 minutes, including a Q&A. Furthermore, we’ve scheduled five hands-on workshops, each about one and a half hours.
The event is set for the 28th of October, and registration is open! You can register here!
One challenge we’ve contemplated is the shift from online to a physical format. During online events, it was easier to involve international figures or speakers. But with our event now taking place in Kuala Lumpur, the capital of Malaysia, travel becomes a concern. Thankfully, we have some generous sponsors and consultants helping us, including help from the R Consortium. We’re offering travel and accommodation allowances for our speakers, ensuring they can join and present in person.
At the R confeRence 2023 this year, who is speaking, and what is the focus?
Regarding this year’s topics and speakers, we’re focused on four main themes:
- Machine Learning: An exploration of R’s capabilities in the realm of predictive analytics.
- Epidemiology and Medical Statistics: We’re particularly excited about this, as we’ve partnered with a prominent medical school in northern Malaysia. This theme will feature speakers primarily from public health backgrounds who utilize R for their analyses.
- Data Visualization: R is renowned for its data visualization strengths, and this theme will delve into the latest techniques and best practices.
- Data Management and Deployment: The final theme will address the challenges and solutions in handling and deploying data using R.
These are our central themes, and we’re thrilled to have a diverse group of speakers representing each of them this year.
Regardless of the industry someone hails from, attending offers a unique chance to gain insights, network with R professionals, and learn from the best in the field.
Please share about a project you are currently working on or have worked on in the past using the R language. Goal/reason, result, anything interesting, especially related to the industry you work in.
I’m currently a senior manager at British American Tobacco (BAT). In the data analytics department, our primary focus is on Revenue Growth Management (RGM). One of my personal projects is developing a Marketing Mix Modeling (MMM) tool. Essentially, this tool analyzes promotions across various channels and calculates the return on investment (ROI) from marketing expenditures for each channel.
I’ve chosen to build this tool using R because it offers powerful libraries, particularly for time series analysis. I’m also integrating various R packages into the tool to enhance its capabilities. Once I’ve completed this tool, my goal is to present it to my superiors as a valuable resource for assessing the effectiveness of our marketing investments across different products and channels in the company.
What resources/techniques do/did you use? (Posit (RStudio), Github, Tidyverse, etc.)
I’m increasingly relying on cloud platforms for my work. For instance, I frequently use Google Colab because it’s a convenient environment to execute R code. It offers the advantage of running code without any local installations, which is highly beneficial, especially when giving presentations.
Before this, I was using RStudio Cloud, now renamed RStudio Workbench.
Two months ago, I gave a talk on the mlr3 R package. This package addresses a challenge in R: the presence of multiple packages with overlapping functionality. In the realm of Python machine learning, there’s a standard library called scikit-learn, which provides comprehensive end-to-end machine learning tools. I believe R needs something similar, and that’s where the mlr3 library shines. It’s a unified package for training machine learning models in R, and I introduced it in my talk.
When I deliver talks, I choose Google Colab as my go-to platform, primarily because it’s stable and user-friendly. I simply share a Colab link with participants, allowing them to run and interact with the code directly in their browsers without any installations.
For reference, I can share the recording of my “mlr3” presentation along with the associated Google Colab notebook:
- MLR3 Colab Notebook: https://colab.research.google.com/drive/1zie1L345EYKuO5A3Nr4DQ34kRDyPSGVJ?usp=sharing
- Video Recording: https://www.youtube.com/watch?v=npNRiOhw_ws
- Run R code in the cloud: https://colab.research.google.com/?utm_source=scs-index
Is this an ongoing project? Please share any details or ways for someone to get involved!
Currently, it’s still in progress and not ready for public sharing. Once it’s complete, I’ll provide the GitHub link. Our goal is to make it open source, allowing others to view and contribute.
What trends do you currently see in R language and your industry? Any trends you see developing in the near future?
In our data analytics industry, many professionals are gravitating towards Python. It’s essential to continuously demonstrate R’s capabilities, emphasizing that it can perform many tasks at which Python excels. We should leverage the latest technologies that spark excitement and interest to showcase the benefits of using R. It’s a user-friendly language that provides machine learning and production-grade application development tools.
In the past, we’ve demonstrated R’s compatibility with TensorFlow, PyTorch, and other tools. While Python has strengths, one can still achieve impressive results with R without delving deep into complex programming.
Looking ahead, our objective should be to ensure no noticeable difference in applications developed using either Python or R. The workflow should be consistent regardless of the chosen language. For instance, the Shiny platform now supports both R and Python and regardless of which language it’s written in, the output remains consistent in appearance and functionality. The key is achieving uniformity across platforms and results.
How do I Join?
R Consortium’s R User Group and Small Conference Support Program (RUGS) provides grants to help R groups worldwide organize, share information and support each other. We have given grants over the past four years, encompassing over 65,000 members in 35 countries. We would like to include you! Cash grants and meetup.com accounts are awarded based on the intended use of the funds and the amount of money available to distribute. We are now accepting applications!