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turned_in Stanford CS229 - Machine Learning

Classic

  • 01. Course Synopsis

    • Materials

  • picture_as_pdf cs229-notes1.pdf
  • picture_as_pdf cs229-notes2.pdf
  • picture_as_pdf cs229-notes3.pdf
  • picture_as_pdf cs229-notes4.pdf
  • picture_as_pdf cs229-notes5.pdf
  • picture_as_pdf cs229-notes6.pdf
  • picture_as_pdf cs229-notes7a.pdf
  • picture_as_pdf cs229-notes7b.pdf
  • picture_as_pdf cs229-notes8.pdf
  • picture_as_pdf cs229-notes9.pdf
  • picture_as_pdf cs229-notes10.pdf
  • picture_as_pdf cs229-notes11.pdf
  • picture_as_pdf cs229-notes12.pdf
  • picture_as_pdf cs229-notes13.pdf

    • Posts

  • [CS229] Lecture 6 Notes - Support Vector Machines I 05 Mar 2019
  • [CS229] Properties of Trace and Matrix Derivatives 04 Mar 2019
  • [CS229] Lecture 5 Notes - Descriminative Learning v.s. Generative Learning Algorithm 18 Feb 2019
  • [CS229] Lecture 4 Notes - Newton's Method/GLMs 14 Feb 2019
  • [CS229] Lecture 3 Notes - LWR/Prob Interp/Logistic/Perceptron 12 Feb 2019