• Handout 0 About the course
• Lecture 1 Computing. What's in a name? (8 pages)
• Lecture 2 A very basic intro to python (stump, 2 pages) currently only logging in
  pythondemo.py
  demoplot1.py
• Lecture of 4/4 Some data structs in python
• Data structures
  Lecture of 4/9 Data structures basics (unedited)
  Lecture of 4/11 Binary trees (unedited)
  sh2-stack-queue.pdf
  sh3-tree-search.pdf
  sh4-empty-tree.pdf
  sh4.1-example-tree.pdf sh4.1-example-tree.tex Edit this tex file to create tree drawings. Compile it to .pdf with this command file (see more in the lecture template below).
• Lecture 3 The shortest path algorithm
• Lecture 4 Radix trees
  Lecture of 4/16 Binary trees and radix trees (unedited)
• Lecture 5 Data structures for indexing large data sets
  Lecture of 4/18 Kernel density estimation, regression and classification; kd-trees
• Data structure for disjoint sets
  Lecture of 4/23 Data structures for disjoint sets (unedited)
  sh5-disjoint-sets.pdf
  sh5.1-points.pdf
• Lecture 6 Hashing and hash functions
  Lecture of 4/25 Hashing and hash functions
• Lecture 7 Markov chains
• Lecture 8 Summary of Hidden Markov Models algorithms
  Lecture of 4/30 Markov chains
  A tutorial on HMM by L. Rabiner
  sh-hmm.pdf
  sh-viterbi.pdf
  Lecture of 5/2 HMM Forward-Backward
  Lecture of 5/7 HMM Baum-Welch
  Lecture of 5/9 HMM Viterbi and DP
• Lecture 9 Dynamic programming -- a computational perspective (TB posted!)
  sh7-longest-common-subseq.pdf
  sh7-longest-common-subseq-empty.pdf
  sh-matrix-mult.pdf
• 0514_python_plotting.zip Plotting with Matplotlib Lecture by Yu-chia Chen (24 MB) (click here to retrieve separate files)
• MCMC notes (4 pages, handwritten)
  Intro to Markov Chain Monte Carlo Algorithms (notes by Alistair Sinclair) -- May 31 lecture
  MC and MCMC slides (13 pages) by Adrian Dobra
  Volume of a convex body (bookchapter by Mark Jerrum) -- May 31 lecture
  Lecture of 5/21 Gibbs sampling
  Lecture of 5/28 Rejection sampling, importance sampling, Metropolis-Hastings
• Lecture 11 Markov Random Fields and Iterative Proportional Fitting
  Lecture of 5/28 MRF, IPF, BW with multiple sequences

  Lecture templates

  lecture-template.tex and lecture-template.pdf

  Old course notes

• h2-instructions.txt Using the virtual machine to run C programs
• Handout 3 Kernel density estimation
• Handout 2 Static sets
• Handout 3 How to write good code
• Handout 4 Dynamic sets
• Handout 6 Notes on MCMC
• h5-howto-rng.txt Generating random numbers
  the files you need to download are here and this is and example of usage: example_rand.c
• The Inside-Outside Algorithm

C examples

• test-printf.c on formats for printing decimal numbers
• smallio.c variations on getline and reading to the end of file (EOF)
• stat534_rand and example_rand.c
• example_fileread.txt
• example-99reals.dat stack.h.txt
  stack.c.txt
  
• example C code with arrays