What we’re about
Hello and a warm welcome to the Karachi R User Group!
R is an open-source programming language for statistical computing and data science - from data mining, cleaning, wrangling, exploration, machine learning, and communication.
R is commonly used in both academia, in fields like computational biology and applied statistics, and in commercial areas such as healthcare, quantitative finance, geospatial applications, and business intelligence.
We're thrilled to have you here with us. Our mission is to foster a vibrant and inclusive community of R programming enthusiasts. Whether you're a seasoned R pro or just starting, you will learn from this community.
Karachi R User Group is a non-profit platform. We're all about sharing knowledge, networking, and supporting each other on our R journey. We regularly organize R programming training sessions, meetups, and workshops to help you enhance your skills and stay connected with like-minded individuals.
As our group grows, you can look forward to a variety of engaging talks. We'll have sessions for R beginners looking to get a solid start, and professionals sharing their personal growth stories. Topics will span from Data Analysis, Data Visualization, and Shiny Application Development, to Statistical and Data Science Programming, and so much more!
If you're eager to share your own R journey or expertise, we'd love to hear from you. Please reach out to Uzair Aslam at m.uzair@statdevs.com. Your unique story and insights can inspire and enrich our community.
You can also join our WhatsApp Group to stay connected with R User Karachi Community: https://chat.whatsapp.com/Fls9OuTBQqn4ihJ16VZa3Y
Thank you for joining us, and let's embark on this R adventure together!
Upcoming events (1)
See all- Model-Assisted Small Area Estimation Using Mixed-Effects Random ForestsLink visible for attendees
We are looking forward to the July edition of the Karachi R User Meetup, sponsored by Stat Devs and R Consortium
Agenda for the Talk:
Join the Karachi R User Group for an insightful talk on “Model-Assisted Small Area Estimation Using Mixed Effects Random Forest” presented by Muhammad Hamza.
This session will unpack the need for Small Area Estimation (SAE), the advantages of using ML algorithms over traditional methods, and the key distinctions between unit-level and area-level models.
We’ll explore design-based, model-based, and model-assisted frameworks, with a focus on implementing Mixed-Effects Random Forests in R. Practical applications using health indicators from the Demographic and Health Surveys (DHS) will also be showcased.
Whether you’re a data scientist, statistician, or policymaker, this talk will offer valuable insights into producing reliable estimates for data-limited regions with hands-on experience in R.
