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What is the best system for experimenting with and visualizing complex algorithms?Let's say you see a sophisticated algorithm in a textbook, with a precise definition in terms of highlevel operations. For example, in his textbook on Machine Learning, AlpaydÄ±n derives an algorithm for finding the highest probability state sequence for a Hidden Markov Model given an observation sequence. The algorithm has a precise definition but it is very high level and it leans heavily on the accompanying mathematical derivation. All of the implementation details are left out. I would like to code the algorithm, combine it with other algorithms, and make variations. I would like to test the algorithm and visualize its results. More broadly, I would like to experiment with machine learning and knowledgeintensive algorithms. My goal is to understand the possibilities and limitations of machine learning. (But other people might have other goals with such a system.) What's a good system for doing this? Ideally, the system should have a welldesigned core language (including lexical scoping, good concurrency model, closures, factored design, etc.), have a good set of combinators for building algorithms and good libraries for all the most useful high level operations, be interactive and easy to use, have a good I/O ability including reading and writing concurrent streams and interactive visualization, and be reasonably efficient. This is a tall order. Should I look at a computer algebra system (e.g., Mathematica, Maple, or Sage) to satisfy these requirements? What experience do LtU members have? By Peter Van Roy at 20100920 14:48  LtU Forum  previous forum topic  next forum topic  other blogs  4964 reads

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