Some notes I've taken, and other files. All links are to PDFs.

• Miscellaneous
  
  • linear algebra review
  • probability review
  • least squares linear regression by gradient descent
• ESL
  My notes on The Elements of Statistical Learning by Friedman, Tibshirani, and Hastie.
  • chapter 2: least squares and nearest neighbors
  • bias-variance decomposition
  • chapter 2 exercises
  • linear regression
  • multivariate linear regression
  • chapter 4: linear methods for classification notes
  • chapter 7: model selection and assessment notes
• CS229
  My notes on the Stanford CS229 machine learning course.
  • lecture 1 notes
  • lecture 2 notes
  • lecture 3 notes
  • lecture 4 notes
  • boosting notes
  • convex optimization notes
  • general loss function notes
  • Hoeffding inequality notes
  • problem set 0
  • problem set 1
  • problem set 2
• Deep learning book
  My notes on Deep Learning by Goodfellow, Bengio, and Courville.
  • chapter 4: numerical computation notes
  • chapter 5: machine learning basics notes
  • chapter 6: deep feedforward networks notes
• PhD dissertation
  My dissertation: "Genomic analyses of transcription elongation factors
  and intragenic transcription".
  • dissertation
  • presentation