Forecasting Time Series with Linear Regression: A Feature-Driven Approach

Hands-on session with Rami Krispin

Beginner-friendly workshop led by author and open source contributor Rami Krispin, exploring time series forecasting through linear regression and feature engineering.

Registered Attendees (125)

On July 03, 2025, R-Ladies Rome hosted a practical and beginner-friendly workshop titled “Forecasting Time Series with Linear Regression: A Feature-Driven Approach.” The session was led by Rami Krispin, author of Hands-On Time Series Analysis with R and an expert in time series forecasting at scale.

📊 Workshop Overview

This talk explores the fundamentals of time series forecasting using linear regression models. We’ll cover how to transform time series data into a supervised learning format and utilize feature engineering techniques to model various components of the series, including trends, seasons, outliers, and structural breaks. This is a beginner-level workshop, and prior knowledge of time series is not needed beyond understanding how linear regression works.

🎥 Recording

🎬 Watch the Video Now

Whether you’re brushing up on regression or just getting started with time series, this session is packed with practical insight and real-world examples.

🧠 What You’ll Learn

• How to frame time series as a supervised learning problem
• Why feature engineering matters: trends, seasonality, outliers, and breaks
• How to apply linear models to time-dependent data
• Tips for model validation and performance assessment

📦 Resources & Materials

🔗 Slides & resources: https://github.com/RamiKrispin/r-ladies-rome-workshop

🌐 Learn more:

• Rami’s Book: https://ramikrispin.github.io/atsaf/

• Rami’s Book Hands-On Time Series Analysis with R: Perform time series analysis and forecasting using R:

  • https://github.com/RamiKrispin
  • https://www.amazon.com/dp/1788629159

📝 R-Ladies Rome Intro Presentation: https://rladiesrome.quarto.pub/july032025

📅 Stay updated: https://www.meetup.com/rladies-rome

🔊 About the Speaker

Rami Krispin leads the data science and engineering team at Apple Finance - Services and Infra. His team builds advanced statistical and ML models to support Apple’s strategic decisions. Rami is also an open-source contributor and author, with a special focus on scalable forecasting tools. He’s currently working on his next book: Applied Time Series Analysis and Forecasting.

💬 Keep learning and sharing—subscribe to our YouTube channel and check out more past events on rladiesrome.org!

#TimeSeries #Forecasting #RStats #RLadiesRome #LearningTogether #RamiKrispin

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