Linear Models, Training

CSI 5180 - Machine Learning for Bioinformatics

Important

I have now published the descriptions for both the presentation and the project on the course website. You can access them through the following links:

• Presentation Description (selection due: February 7, 2025)
• Project Description (outline due: Febrary 14, 2025)

Prepare

You might want to watch or re-watch the following video.

• Why Linear regression for Machine Learning? (3m 58s)
• StatQuest with Josh Starmer
  • Linear Regression, Clearly Explained!!! (27m 26s)
  • Gradient Descent, Step-by-Step (23m 53s)
• Herman Kamper 8 videos on Linear Regression
• Andrew Ng¹
  • Gradient Descent (Math) (11:30 m)
  • Intuition (11:51 m)
  • Linear Regression (10:20 m)
  • ML-005 | Stanford | Andrew Ng (19 videos)

Mathematics

• 3Blue1Brown
  • Essence of linear algebra
    • A series of 16 videos (10 to 15 minutes per video) providing “a geometric understanding of matrices, determinants, eigen-stuffs and more.”
      • 6,662,732 views as of September 30, 2019.
  • Essence of calculus
    • A series of 12 videos (15 to 20 minutes per video): “The goal here is to make calculus feel like something that you yourself could have discovered.”
      • 2,309,726 views as of September 30, 2019.

Participate

• slides

Practice

Three notebooks from Aurélien Géron introducing essential concepts for machine learning. In the coming weeks, you might want to go through these at your own pace.

• numpy – a fundamental library centered around N-dimensional array objects.
• pandas – powerfull data analysis tools, centered around the DataFrame.
• visualization – demonstrates how to use the matplotlib to produce beautiful graphs.

Footnotes

1. Andrew Ng is Founder of DeepLearning.AI, Founder & CEO of Landing AI, General Partner at AI Fund, Chairman and Co-Founder of Coursera and an Adjunct Professor at Stanford University’s Computer Science Department.

   Ng was also a cofounder and head of Google Brain and was the former Chief Scientist at Baidu.