David MacKay
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Information Theory, Pattern Recognition and Neural Networks

Part III Physics Course: Minor option. 12 lectures.

What's new, 2009:

  1. Lecture times: Mondays and Wednesdays, 2pm, starting 26th January. Pippard Lecture Theatre
  2. Course synopsis: | Handout 1 (2 pages postscript) | pdf |
  3. Handout 2: | Handout 2 (2 pages postscript) | pdf |

What's new, 2008:

  1. Course synopsis: | Handout 1 (2 pages postscript) | pdf |
  2. Handout 2: | Handout 2 (2 pages postscript) | pdf |

What's new, 2007:

  1. Course synopsis: | Handout 1 (2 pages postscript) | pdf |
  2. Handout 2: | Handout 2 (2 pages postscript) | pdf |
  3. Handout 3: | Handout 3 (1 pages postscript) | pdf |
  4. PAST PAPERS: || Papers from 2004, 2005, 2006, with some worked solutions (postscript) (pdf) | | The whole 2006 paper (pdf) | | 2001 questions | & solutions |
  5. | solutions for 2007 |
  6. Slides for lectures 1-12 are available on line.
  7. perl program for Huffman algorithm: huffman.p
    python programs for Huffman algorithm: huffman10.py
    Bent coin: a sparse file containing N=10000 bits of which roughly 0.01 are 1s.

The main thing at this site is the free on-line course textbook Information Theory, Inference and Learning Algorithms, (which also has its own website).

An old (2006) incarnation of this website is here


Want to ask a question?

- please click to see the FAQ about the book, the course, or the software.

Want to give feedback on the book, or report typos?

Great, to ask a question about the book please use this FAQ; to report a typo, mail me. THANK YOU! List of corrections already reported

Site last modified Sun Aug 31 18:51:05 BST 2014

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