MIT 15.071 The Analytics Edge, Spring 2017 6.4.1 Welcome to Recitation 6 - Seeing the Big Picture: Segmenting Images to Create Data
6.4.1 Welcome to Recitation 6 - Seeing the Big Picture: Segmenting Images to Create Data Transcript and Lesson Notes
MIT 15.071 The Analytics Edge, Spring 2017 View the complete course: https://ocw.mit.edu/15-071S17 Instructor: Nataly Youssef Review of hierarchical and k-means clustering techniques, and uses, pros, and cons of all the
Quick Summary
MIT 15.071 The Analytics Edge, Spring 2017 View the complete course: https://ocw.mit.edu/15-071S17 Instructor: Nataly Youssef Review of hierarchical and k-means clustering techniques, and uses, pros, and cons of all the
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: Nataly Youssef Review of hierarchical and k-means clustering techniques, and uses, pros, and cons of all the
- Understand how MRI images fits into 6.4.1 Welcome to Recitation 6 - Seeing the Big Picture: Segmenting Images to Create Data.
- Understand how MRI brain scan fits into 6.4.1 Welcome to Recitation 6 - Seeing the Big Picture: Segmenting Images to Create Data.
- Understand how segmenting fits into 6.4.1 Welcome to Recitation 6 - Seeing the Big Picture: Segmenting Images to Create Data.
- Understand how gray scale images fits into 6.4.1 Welcome to Recitation 6 - Seeing the Big Picture: Segmenting Images to Create Data.
Key Concepts
Full Transcript
MIT 15.071 The Analytics Edge, Spring 2017 View the complete course: https://ocw.mit.edu/15-071S17 Instructor: Nataly Youssef Review of hierarchical and k-means clustering techniques, and uses, pros, and cons of all the analytics tools that we have covered in the class so far. 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 6.4.1 Welcome to Recitation 6 - Seeing the Big Picture: Segmenting Images to Create Data about?
MIT 15.071 The Analytics Edge, Spring 2017 View the complete course: https://ocw.mit.edu/15-071S17 Instructor: Nataly Youssef Review of hierarchical and k-means clustering techniques, and uses, pros, and cons of all the
What key concepts are covered in this lesson?
The lesson covers MRI images, MRI brain scan, segmenting, gray scale images.
What should I learn before 6.4.1 Welcome to Recitation 6 - Seeing the Big Picture: Segmenting Images to Create 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: MRI images, MRI brain scan, segmenting, gray scale images.
Does this lesson include a transcript?
Yes. The full transcript is visible on this page in indexable HTML sections.
Is this lesson free?
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