Name: BARUG March 2025 Meeting
Start: 2025-03-13T18:30:00-07:00
End: 2025-03-13T20:45:00-07:00
Location: Thermo Fisher Scientific

The meeting is still coming together, but we are excited to announce our first meetup of the year. Please mark Thursday evening, March 13 on your calendar.

Agenda:
6:30 Pizza and networking
7:05 Announcements
7:15 Simon Cawley: Biotech and Data Science at Thermo Fisher
7:30 Mariana Menchero, author of the nixtlar R package will speak about time series forecasting with TimeGPT
8:10 Rami Krispin will talk about time series forecasting with R.

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**Mariana Menchero**
**Time Series Forecasting with TimeGPT**

**Abstract:**
In this talk, I’ll explain how TimeGPT works and how it can be used in R via the nixtlar package. I’ll introduce foundation models and explain the transformer architecture, the basis of TimeGPT. I’ll then show how to use nixtlar effectively with a retail dataset and apply its key features, including fine-tuning, exogenous variables, prediction intervals, and anomaly detection. I’ll conclude with a summary of the strengths and weaknesses of foundation models and how TimeGPT can be incorporated into R workflows for effective forecasting.

**About Mariana**
I’m a Senior Forecaster at Nixtla and the developer of nixtlar, an R package that interfaces with Nixtla’s TimeGPT, the first foundation model for time series forecasting. I hold a MIT Micromasters credential in Supply Chain Management and a B.S. in Applied Mathematics. I’ve been a forecasting enthusiast since 2019 and I'm passionate about building forecasting tools for the R and Python communities.

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**Rami Krispin**
**Analyzing Time Series at Scale with Cluster Analysis**

**Abstract**
One of the challenges in traditional time series analysis is scalability. Most of the analysis methods were designed to handle a single time series at a time. In this talk, we will review methods for analyzing time series at scale using unsupervised learning methods. We will demonstrate how to apply cluster analysis and PCA to analyze and extract insights from multiple time series simultaneously. This talk is based on Prof. Rob J Hyndman's paper about feature-based time series analysis.

**About Rami**
Rami Krispin is a data science and engineering manager who mainly focuses on time series analysis, forecasting, and MLOps applications.
He is passionate about open source, working with data, machine learning, and putting stuff into production. He creates content about MLOps and recently released a course - [Data Pipeline Automation with GitHub Actions Using R and Python](https://www.linkedin.com/learning/data-pipeline-automation-with-github-actions-using-r-and-python), on LinkedIn Learning, and is the author of [Hands-On Time Series Analysis with R](https://www.packtpub.com/product/hands-on-time-series-analysis-with-r/9781788629157?source=about_page-------------------------------------).

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BARUG March 2025 Meeting

Thermo Fisher Scientific

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BARUG March 2025 Meeting

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