What we’re about
The Southern California R Users Group (SoCal RUG) Meetup Group explores and discusses R and how it is being used in data science, data analysis, visualization, data mining, predictive analytics, and beyond. People of all levels are welcome to attend, from those just getting started with R and predictive modelling to experts using R every day.
Links to our resources: https://linktr.ee/socalrug
Email: orangecounty.rug@gmail.com
Donate: SoCal R is a not for profit organization, you can donate here
All participants agree to abide by the SoCalRUG's Code of Conduct
Sponsors
See allUpcoming events (3)
See all- Navigating the Present and Defining the Future of GenAI in ProductionInterdisciplinary Science and Engineering Building (ISEB), Irvine, CA
Navigating the Present and Defining the Future of GenAI in Production
**REGISTRATION: SIGN-UP VIA LUMA**The UC Irvine Master of Science in collaboration with Southern California R Users Group is hosting a dynamic panel conversation on exploring the practical and operational challenges of implementing GenAI in production as well as its current use.
Each of our panelists will share their experiences and insights within their respective organizations. The panel will provide a view of the current state of GenAI in production environments.
Our goal is to stimulate thoughtful conversation and exchanges of ideas among panelists and audience members. We strive to foster a nuanced understanding of the current landscape of GenAI in production and anticipate its future directions.
Panelists:
- Lizzy Kang, BI Engineer | Amazon
- Ryan Romeos, Director of Global Marketing | HP
- Khiry Kemp, Head of Operations | Stemuli | (Black Founders Initiative Chair for Founders Network)
Moderator:
- Javier Orraca-Deatcu, SoCal RUG
Not open - Supervised Machine Learning Techniques with R **Sign-up on EVENTBRITE**The Paul Merage School of Business, Irvine, CA
** SIGN-UP on Eventbrite** The Meetup Event will be locked **
SUPERVISED MACHINE LEARNING TECHNIQUES WITH R
In this workshop, we'll study supervised machine learning methods using R. We’ll cover both the theoretical foundations and practical implementations of various techniques. These include statistical methods like decision trees, random forests, and naïve Bayes classification, alongside mathematical optimization techniques such as gradient boosting, k-nearest neighbors, support vector machines, and artificial, recurrent, and convolutional networks. If time allows, we'll also explore the fascinating world of natural language processing. Data sets and complete R codes will be provided.Not open