MIT 15.071 The Analytics Edge, Spring 2017 4.4.1 Welcome to Recitation 4 - Location, Location, Location: Regression Trees for Housing Data
4.4.1 Welcome to Recitation 4 - Location, Location, Location: Regression Trees for Housing Data Transcript and Lesson Notes
MIT 15.071 The Analytics Edge, Spring 2017 View the complete course: https://ocw.mit.edu/15-071S17 Instructor: Iain Dunning Applying regression trees to Boston house price data. License: Creative Commons BY-NC-SA More in
Quick Summary
MIT 15.071 The Analytics Edge, Spring 2017 View the complete course: https://ocw.mit.edu/15-071S17 Instructor: Iain Dunning Applying regression trees to Boston house price data. License: Creative Commons BY-NC-SA More in
Key Takeaways
- Review the core idea: MIT 15.071 The Analytics Edge, Spring 2017 View the complete course: https://ocw.mit.edu/15-071S17 Instructor: Iain Dunning Applying regression trees to Boston house price data. License: Creative Commons BY-NC-SA More in
- Understand how visualizations fits into 4.4.1 Welcome to Recitation 4 - Location, Location, Location: Regression Trees for Housing Data.
- Understand how models fits into 4.4.1 Welcome to Recitation 4 - Location, Location, Location: Regression Trees for Housing Data.
- Understand how data fits into 4.4.1 Welcome to Recitation 4 - Location, Location, Location: Regression Trees for Housing Data.
Key Concepts
Full Transcript
MIT 15.071 The Analytics Edge, Spring 2017 View the complete course: https://ocw.mit.edu/15-071S17 Instructor: Iain Dunning Applying regression trees to Boston house price data. License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu
Lesson FAQs
What is 4.4.1 Welcome to Recitation 4 - Location, Location, Location: Regression Trees for Housing Data about?
MIT 15.071 The Analytics Edge, Spring 2017 View the complete course: https://ocw.mit.edu/15-071S17 Instructor: Iain Dunning Applying regression trees to Boston house price data. License: Creative Commons BY-NC-SA More in
What key concepts are covered in this lesson?
The lesson covers visualizations, models, data.
What should I learn before 4.4.1 Welcome to Recitation 4 - Location, Location, Location: Regression Trees for Housing Data?
Review the previous lessons in MIT 15.071 The Analytics Edge, Spring 2017, then use the transcript and key concepts on this page to fill any gaps.
How can I practice after this lesson?
Practice by applying the main concepts: visualizations, models, data.
Does this lesson include a transcript?
Yes. The full transcript is visible on this page in indexable HTML sections.
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