Feature Engineering for Time Series Projects - I
Learn important concepts of Feature Engineering and Intervention Analysis with Python codes walkthrough.
Prabhakaran SPrincipal Data Scientist
Included in All-Access, one membership for every course.
- Lessons
- 19
- Video
- 1 h 28 min
- Free to watch
- 1 lesson
- Certificate
- On completion
Course content
1 chapter · 19 lessons · 1 h 28 min · 1 free to preview
01Feature Engineering and Intervention Analysis for Time Series Projects - Part 119 lessons · 1 h 30 min
- Feature Engineering and Intervention Analysis for Time Series Projects - Part 18:00
- Why Do we need Feature EngineeringPreview7:52
- Download Resources1:00
- Setup and Import Datasets4:02
- Date Time Features4:18
- Create Country specific Holidays10:57
- Lag Features9:38
- Window Features7:02
- Cyclical Features4:40
- Box Cox Transformation5:02
- Course Review1:00
- Moving Averages3:15
- How to find the appropriate window length of MA2:56
- Lowess3:58
- Classical Decomposition2:08
- STL Seasonality1:59
- MSTL3:30
- Fourier Transforms2:19
- Types of Features6:31
What you need
- Basics of Python
- Foundational knowledge of Data Science
- High school maths
Who this course is for
- Data Science Aspirants
- Data Science Professionals
- Software/Data engineers interested in quantitative analysis
- Professionals working with large datasets
- Data analysts, economists, researchers
Your instructor

Prabhakaran S
Principal Data Scientist
My name is Selva, and I am super excited to mentor you on this course!
I head the Data Science team for a global Fortune 500 company and over the last 10 years of my data science experience I've deployed 20+ global products. I'm also the Founder and Chief Author of Machine Learning Plus, which has over 4M annual readers.
I specialize in covering the in-depth intuition and maths of any concept or algorithm. And based on my existing student requests, I've put up the series of courses and projects with detailed explanations, just like on-the-job experience. Hope you love it!
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Questions
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