Nov 6 2024

(Stanford - Linear Regression)

  • Finished Artificial Intelligence & Machine Learning 2 - [Linear Regression Stanford CS221: AI (Autumn 2021)](https://www.youtube.com/watch?v=nEWNNt2KmfQ)
    • Went through the video…understood the overall concept
    • Went through it again, made sure I could do the math.
    • At 4:50-ish [here→ Artificial Intelligence & Machine Learning 2 - Linear Regression Stanford CS221: AI (Autumn 2021)](https://youtu.be/nEWNNt2KmfQ?si=O0fPJKKyTxmRfNtz&t=296)
      • I had to spend some time understand that I’m multiplying a weighted vector by a feature vector. And that the equations above match what he re-writes them all to by using the dot product of vectors.
      • Went through the math for each step, did the actual math to arrive at each of the numbers
    • Typed out the python too.

(Fast.ai) Started Fast.ai’s Practical Deep Learning for Coders - just the video

  • Training is based on having experiences and context – like learning a sport, you have the kids play it and you don’t cover all the rules up front.
  • I liked that I understood the Stanford linear regression topic because it helped me understand some of the topics that Fast.ai went through quickly (but they talk a lot about going deeper later)