What Next? From January 2018
- Start Seven More Languages in Seven Weeks in January 2018
- Next meeting on 5th December: interstitial
- Show and tell of random things you have done that are
- Computationy
- Somewhat festive?
- Make pies
- Some sort of festive algorithm bake-off
- Travelling Santa problem
- Fractal christmas tree
- Festive shaders
- Awkward staring at crisps
- https://github.com/computationclub/turing-challenge
- https://github.com/computationclub/christmas-problems
- 19th December meeting is unlikely to happen
- Maybe a computation.pub?
- Gödel, Escher, Bach
- Seven More Languages in Seven Weeks
- Implementing a language (e.g. Lambda Calculus)
- Modern Compiler Implementation in
$lang - 3D Graphics
- Machine Learning
- Programming Collective Intelligence
- Neural Networks and Deep Learning
- Complexity Theory
- Computer Vision
- Foundations of Statistical Natural Language Processing
10 PRINT CHR$(205.5+RND(1)); : GOTO 10- Code: The Hidden Language of Computer Hardware and Software
- The Annotated Turing
- The Art of Prolog
- 10 Technical Papers Every Programmer Should Read (At Least Twice)
- Category Theory for Programmers
- Cryptopals
Thanks to Charlie for hosting, to Chris for organising the meeting, to everyone who suggested a topic, Simon for driving and taking notes and to all those who brought snacks and drinks.
We're going to meet on 21st Nov 2017 to decide what the club should focus on from January 2018 (in the interim we plan to do one-off meetings or similar).
This page can be used to collect and expand on ideas. If you're even slightly interested in attending, your ideas are very welcome! They don't have to be specific books or papers you'd like to read - they can be subject areas you're interesting, e.g. "3D graphics". Let us know even if you can't make the decision meeting, and we'll try to capture everyone's input.
See the last two "what's next" pages for things we've previously considered:
- 3D Graphics
- What even is a shader?
- General-purpose GPU computing
- Book / Source options:
- Game algorithms
- Map generation
- Primitive AI (but why limit ourselves?)
- Book / source options:
- How git works
- Event sourcing
- The Nile graphics language
- How to actually implement a lambda calculus
- We've done this using term rewriting, but it doesn't usually work like that. To quote @tomstuart "it doesn’t admit any real notion of “compilation” — your runtime representation is a term. [Whereas] what you really want is to define (spoilers) some kind of abstract machine whose semantics exactly match those of the term rewriting we’ve seen, but does it in less space and time and without needing to manipulate raw ASTs"
- See: https://en.wikipedia.org/wiki/SECD_machine
- Probabilistic Parsing [charlie], book idea
- Automatic Text Summarization [charlie], [no book idea]
- Logic Programming [joel], book idea
- Complexity theory and combinatorics
- Cook-Levin theorem
- Super Mario Bros Proved NP-Hard
- Four colour theorem
- God's algorithm
- The Witness
- Computer vision
- Machine learning
- Linear / logistic regression
- Neural networks
- Support vector machines
- To Mock a Mockingbird
- 10 papers every programmer should read at least twice (the original (the repost))
- 10 technical papers every programmer should read at least twice (the spiritual sequel)
- Category Theory for Programmers
- Write yourself a Scheme in 48 hours
- Seven
${THING}s in seven weeks - Godel Escher Bach
- A couple of possibilities in the machine learning field:
- Haskell [adzz]
- Browser tech, in particular canvas / webgl [Simon C]