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Feature Engineering for Time Series Forecasting - Kishan Manani
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In this podcast episode, we talked with Kishan Manani about feature engineering for time series forecasting.
0:00 Introduction and Welcome
2:16 Speaker Introduction
2:54 Topic Introduction: Feature Engineering for Time Series Forecasting
4:23 Motivating Example: M5 Forecasting Competition
6:25 Machine Learning for Time Series Forecasting
8:50 Direct Forecasting vs. Recursive Forecasting
10:50 Creating Lag Features
11:45 Handling Exogenous Variables
15:55 Static Features
18:00 Time Series Cross Validation
20:00 Key Differences in Machine Learning Workflow
21:35 Feature Engineering Overview
23:00 Lag Features and Correlation Methods
29:20 Window Features
32:25 Static Features and Encoding
37:25 Avoiding Data Leakage
39:30 Useful Libraries and Tools
40:30 Example with Darts Library
45:00 Conclusions and Q&A
🔗 USEFUL LINKS
🎙 ABOUT THE PODCAST
At DataTalksClub, we organize live podcasts that feature a diverse range of guests from the data field. Each podcast is a free-form conversation guided by a prepared set of questions, designed to learn about the guests’ career trajectories, life experiences, and practical advice. These insightful discussions draw on the expertise of data practitioners from various backgrounds.
We stream the podcasts on YouTube, where each session is also recorded and published on our channel, complete with timestamps, a transcript, and important links.
📚Check our free online courses
👋🏼 GET IN TOUCH
0:00 Introduction and Welcome
2:16 Speaker Introduction
2:54 Topic Introduction: Feature Engineering for Time Series Forecasting
4:23 Motivating Example: M5 Forecasting Competition
6:25 Machine Learning for Time Series Forecasting
8:50 Direct Forecasting vs. Recursive Forecasting
10:50 Creating Lag Features
11:45 Handling Exogenous Variables
15:55 Static Features
18:00 Time Series Cross Validation
20:00 Key Differences in Machine Learning Workflow
21:35 Feature Engineering Overview
23:00 Lag Features and Correlation Methods
29:20 Window Features
32:25 Static Features and Encoding
37:25 Avoiding Data Leakage
39:30 Useful Libraries and Tools
40:30 Example with Darts Library
45:00 Conclusions and Q&A
🔗 USEFUL LINKS
🎙 ABOUT THE PODCAST
At DataTalksClub, we organize live podcasts that feature a diverse range of guests from the data field. Each podcast is a free-form conversation guided by a prepared set of questions, designed to learn about the guests’ career trajectories, life experiences, and practical advice. These insightful discussions draw on the expertise of data practitioners from various backgrounds.
We stream the podcasts on YouTube, where each session is also recorded and published on our channel, complete with timestamps, a transcript, and important links.
📚Check our free online courses
👋🏼 GET IN TOUCH
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