Tutorial on stochastic simulation in Haskell - haskell

I'd like to use Haskell for stochastic simulation, but I don't know how. I've read Hutton's 'Programming in Haskell', and I'm comfortable writing deterministic functional programs. However, I don't know how to start writing stochastic simulations of the sort that are easy in imperative languages like R or python. Is there a tutorial or primer on this that I could read, or can anyone provide some tips on getting started?

There's a nice self-contained paper Erwig and Kollmansberger: Functional Pearls - Probabilistic Functional Programming in Haskell on this topic. I used this as a starting point for writing a natural language processor based on Hidden Markov Models in Haskell. There's a package that is based on this paper, which also seems to provide a basic interface to R plotting.
There's also an entry on the HaskellWiki with more links to hackage. In particular, the ProbabilityMonads package might be useful for you.

http://learnyouahaskell.com/a-fistful-of-monads#the-list-monad
This small section in Learn You a Haskell talks about using the List monad and functor functions to easily deal with non-determinism. May be a little simplistic depending on what your needs are, but make good use of the tools that are already in the standard library.

Related

Is Haskell suitable as a first language?

I have had previous exposure to imperative languages (C, some Java) however I would say I had no experience in programming. Therefore: treating me as a non-programmer, would Haskell be suitable as a first language?
My interests in Pure Mathematics and CS seem to align to the intention of most Haskell tutorials, and although i can inherently recognise the current and future industry value of imperative programming, I find the potential of functional programming (in as much as it seems such a paradigm shift) fascinating.
I guess my question can be distilled as follows - would a non-programmer have to understand imperative programming to appreciate and fully utilise functional programming?
Some references:
Are there any studies on whether functional/declarative or imperative programming is easier to learn as a first language?
Which programming languages have helped you to understand programming better?
Well, the existence of SICP suggests that functional languages can be used as introductory material. Scheme is perhaps more approachable than Haskell, however.
Haskell seems to have a reputation for being "difficult" to learn, but people tend to forget that classic imperative programming is difficult to learn as well. Many people struggle at first with the concept of assigning a value to a variable, and a surprising number of programmers never actually do become comfortable with pointers and indirect references.
The connections between Haskell and abstract mathematics don't really matter as much as people sometimes assume, but for someone interested in the math anyway, looking at the analogies might provide an interesting bonus.
There has been at least one study on the effects of teaching Haskell to beginner programmers:
The Risks and Benefits of Teaching Purely Functional Programming in First Year. Manuel M. T. Chakravarty and Gabriele Keller. Journal of Functional Programming 14(1), pp 113-123, 2004.
With the following abstract:
We argue that teaching purely
functional programming as such in
freshman courses is detrimental to
both the curriculum as well as to
promoting the paradigm. Instead, we
need to focus on the more general aims
of teaching elementary techniques of
programming and essential concepts of
computing. We support this viewpoint
with experience gained during several
semesters of teaching large first-year
classes (up to 600 students) in
Haskell. These classes consisted of
computer science students as well as
students from other disciplines. We
have systematically gathered student
feedback by conducting surveys after
each semester. This article
contributes an approach to the use of
modern functional languages in first
year courses and, based on this,
advocates the use of functional
languages in this setting.
So, yes, you can use Haskell, but you should focus on elementary, general techniques and essential concepts, rather than functional programming per se.
There are a number of popular books for beginner programmers that also make it an attractive target for teaching these elementary concepts, including:
"Programming in Haskell"
"The Craft of Functional Programming"
Additionally, Haskell is already widely taught as a first language. -- but remember, the key is to focus on the core concepts as illustrated in Haskell, not to teach the large, rich language that is Haskell itself.
I'll go against the popular opinion and say that Haskell is NOT a good first programming language for the typical first-time programmer. I don't think it is as approachable for a raw beginner as imperative languages like Ruby.
The reason for this, is that people do not think about the world in a functional manner. When they see a car driving down the street, they see the same car, with ever-changing mutable state. They don't see a series of slightly different immutable cars.
If you check out other SO questions, you'll see that Haskell is pretty much never mentioned as a good choice for a beginner.
However, if you are a mathematician, or already know enough about programming to understand the value of functional programming, I think Haskell is a fine choice.
So to summarize, I think Haskell is a perfect fit for you, but not a good fit for the typical beginner.
EDIT: Thanks for the insightful comments. Owen's point that people think in a multi-paradigm manner is very true. This strengthens my belief that a multi-paradigm language like Ruby would be easier to pick up, and has the added benefit of exposing the student to both imperative and functional thinking. Haskell is decidedly not multi-paradigm.
Chuck mentioned Haskell's sophisticated type system which is another great point. While I personally prefer statically typed languages, using a dynamic language allows a beginner to ignore that piece of the puzzle until they are curious enough to find out what is going on behind the scenes. Haskell's type system, while elegant, is in your face from day 1.
Eleven reasons to use Haskell as a mathematician
I cannot write it better than that. But to summarize:
Haskell is declarative and mathematics is the ultimate declarative language, which means that code written in Haskell is remarkably similar to what you would write as a mathematical statement.
Haskell is high-level, no need to know details about caches, memory management and all the other hardware stuff. Also that means short programs which is always good.
Haskell is great for symbolic computation, algebra, logic ...
Haskell is pretty :)
To answer your question: you'll have no problem to start with a functional language as a mathematician with no programming experience. Actually it's the better choice, you won't have to repair the brain damage you would get from C/Java/whatever.
You should also check Mathematica. Some people tend to dislike it since it is a commercial closed-source product, but I think it's a pretty good environment for doing mathematics.
If you haven't had any experience at all, it will in fact be easier for you to be productive in functional programming, especially PURE functional programming. I'm an immigrant from imperative to function, I had to deal with having to forget about 80% of what I learned to be productive in Haskell.
In contrast, it's easier to switch from functional to imperative later on.
On one hand, I think Haskell is nice as a first language, but I suppose, for anyone seriously interested in programming, it should be learned in parallel with C or after C (or an assembly). C is necessary to learn what's happening under the hood, what are the costs of doing this and that, and finally appreciate the usefulness of higher level of abstraction and automatic resource management. I think when being exposed to both C (as a low-level imperative language) and Haskell (as a high-level functional language), most students will find Haskell both practical and expressive.
On the other hand, I think that programming is a craft. It is a practical activity, and it is important to learn the joy of creating something new, useful or interesting. So you need to get things done. And the easiest way for this is using a language which has tools for your problems, i.e. libraries for your data formats, algorithms for your kind of problems. And at this point, Python (or Ruby) may be a better choice, because Hackage still lags behind PyPI in many areas (and say, how many days you need to teach a novice to manipulate an image, or to plot charts in Haskell?).
So, my opinion is that some exposure to low-level imperative programming is necessary (to OOP, probably, not). Then you can understand the value of Haskell. But to get things done, and to quickly become productive, Python is a better choice for beginners. Haskell requires a few weeks before it becomes your tool.
I would say that it is suitable as a first language, and that having learned an imperative language first would probably only interfere with the learning process (since it requires lots of unlearning first).
As a caveat, I would add that a functional language principles would probably be best understood by someone with a mathematical background, as the concepts are abstract mathematical ones.
I know that many schools do teach it as a first functional language, but not as a first language.
Yes it is. Real World Haskell is a great way to get into it http://book.realworldhaskell.org/
I would hesitantly say "yes" except for the fact that in learning, finding someone as a mentor or tutor would be a much less daunting task if you chose a more imperative language to start programming. Might I suggest R or Python (with NumPy and SciPy) instead?
No.
It's very easy for a haskell98 program to be clearly understood. LYAH is a great tutorial for people with no experience but trying to prevent a learner from stumbling on extensions x, y z is gona be tricky. Soon they start to explore and become overwhelmed with advanced programming/mathematical concepts which are much harder to understand but need to be understood to read other's code.
If every piece of haskell was written in just haskell'98/'10 I would probably say yes though.
Without necessarily addressing the question as such, I would add: if you find haskell's persnicketiness too hard, do not be discouraged.
There are other programming languages, even functional ones, which are late bound.

Languages for implementing decision trees

What would be a good choice of programming language in which to implement a decision tree? The results of the implementation will be for personal use only, so no need to consider ability to publish etc.
I have heard that Octave is a good option, can anyone explain why a matrix based language is recommended for implementing decision trees?
I have used Standard ML both to implement decision trees and to write a compiler from a domain-specific language into decision trees. I've also compiled similar decision trees into C code.
It really depends what you want to do with decision trees. If you are trying to do something sophisticated or you are trying to make the decision trees especially easy to read and write, I would suggest either creating a domain-specific language or embedding domain-specific operators into Haskell or Standard ML. If you just want to get going, you could start with ML (easier than Haskell for a beginner) and that preserves some options for later.
In general, ML and Haskell are both very good at representing and manipulating trees of all kinds.
I can't explain why someone would recommend a matrix-based language for decision trees.
I am pretty sure that the first decision tree was written in LISP.
Still many such algorithm is still written in LISP.
You can find many documentation if you decide to choose LISP.
Scheme is also a good language for that purpose and it is simpler/smaller than LISP.
Also the learning curve is fast in both languages.
IMHO

Machine learning in OCaml or Haskell?

I'm hoping to use either Haskell or OCaml on a new project because R is too slow. I need to be able to use support vectory machines, ideally separating out each execution to run in parallel. I want to use a functional language and I have the feeling that these two are the best so far as performance and elegance are concerned (I like Clojure, but it wasn't as fast in a short test). I am leaning towards OCaml because there appears to be more support for integration with other languages so it could be a better fit in the long run (e.g. OCaml-R).
Does anyone know of a good tutorial for this kind of analysis, or a code example, in either Haskell or OCaml?
Hal Daume has written several major machine learning algorithms during his Ph.D. (now he is an assistant professor and rising star in machine learning community)
On his web page, there are a SVM, a simple decision tree and a logistic regression all in OCaml. By reading these code, you can have a feeling how machine learning models are implemented in OCaml.
Another good example of writing basic machine learning models is Owl library for scientific and numeric computations in OCaml.
I'd also like to mention F#, a new .Net language similar to OCaml. Here's a factor graph model written in F# analyzing Chess play data. This research also has a NIPS publication.
While FP is suitable for implementing machine learning and data mining models. But what you can get here most is NOT performance. It is right that FP supports parallel computing better than imperative languages, like C# or Java. But implementing a parallel SVM, or decision tree, has very little relation to do with the language! Parallel is parallel. The numerical optimizations behind machine learning and data mining are usually imperative, writing them pure-functionally is usually hard and less efficient. Making these sophisticated algorithms parallel is very hard task in the algorithm level, not in the language level. If you want to run 100 SVM in parallel, FP helps here. But I don't see the difficulty running 100 libsvm parallel in C++, not to consider that the single thread libsvm is more efficient than a not-well-tested haskell svm package.
Then what do FP languages, like F#, OCaml, Haskell, give?
Easy to test your code. FP languages usually have a top-level interpreter, you can test your functions on the fly.
Few mutable states. This means that passing the same parameter to a function, this function always gives the same result, thus debugging is easy in FPs.
Code is succinct. Type inference, pattern matching, closures, etc. You focus more on the domain logic, and less on the language part. So when you write the code, your mind is mainly thinking about the programming logic itself.
Writing code in FPs is fun.
The only problem I can see is that OCaml doesn't really support multicore parallelism, while GHC has excellent support and performance. If you're looking to use multiple threads of execution, on multiple calls, GHC Haskell will be a lot easier.
Secondly, the Haskell FFI is more powerful (that is, it does more with less code) than OCaml's, and more libraries are avaliable (via Hackage: http://hackage.haskell.org ) so I don't think foreign interfaces will be a deciding factor.
As far as multi-language integration goes, combining C and Haskell is remarkably easy, and I say this as someone who is (unlike dons) not really much of an expert on either. Any other language that integrates well with C shouldn't be much trickier; you can always fall back to a thin interface layer in C if nothing else. For better or worse, C is still the lingua franca of programming, so Haskell is more than acceptable for most cases.
...but. You say you're motivated by performance issues, and want to use "a functional language". From this I infer you're not previously familiar with the languages you ask about. Among Haskell's defining features are that it, by default, uses non-strict evaluation and immutable data structures--which are both incredibly useful in many ways, but it also means that optimizing Haskell for performance is often dramatically different from other languages, and well-honed instincts may lead you astray in baffling ways. You may want to browse performance-related topics on the Haskell wiki to get a feel for the issues.
Which isn't to say that you can't do what you want in Haskell--you certainly can. Both laziness and immutability can in fact be exploited for performance benefits (Chris Okasaki's thesis provides some nice examples). But be aware that there'll be a bit of a learning curve when it comes to dealing with performance.
Both Haskell and OCaml provide the lovely benefits of using an ML-family language, but for most programmers, OCaml is likely to offer a gentler learning curve and better immediate results.
It's hard to give a definitive answer on this. Haskell has the advantages that Don mentioned along with having a more powerful type system and cleaner syntax. OCaml will be easier to learn if you coming from almost any other language (this is because Haskell is as function as functional languages get), and working with mutable random access structures can be a little clunky in Haskell. You will also likely find the performance characteristics of your OCaml code more intuitive than Haskell because of Haskell's lazy evaluation.
Really, I would recommend you evaluate both if you have the time. Here are some relevant Haskell resources:
http://hackage.haskell.org/package/hslibsvm
http://hackage.haskell.org/package/HSvm
Real World Haskell: this is a great freely available book for Haskell
Learn You a Haskell: this tutorial is just plain fun to read
Oh, if you look further into Haskell be sure to sign up for the Haskell Beginners and Haskell Cafe lists. The community is friendly and eager to help out newcomers (is my bias showing?).
If speed is your prime concern then go for C. Haskell is pretty good performance wise but you are never going to get as fast as C. To my knowledge the only functional language that has bettered C in a benchmark is Stalin Scheme but that is very old and nobody really knows how it works.
I've written genetic programming libraries where performance was key and I wrote it in a functional style in C. The functional style allowed me to easily parallelise it using OMP and it scales linearly upto 8 cores within a single process. You certainly can't do that in OCaml although Haskell is improving all the time with regards to concurrency and parallelism.
The downside of using C was that it took me months to finally find all the bugs and stop the core dumps which was extremely challenging because of the concurrency. Haskell would probably have caught 90% of those bugs on the first compilation.
So speed at any cost ? Looking back I'd wish I'd used Haskell as I could stand it to be 2 - 3 times slower if I'd saved over a month in development time.
While dons is correct that multicore parallelism at the thread level is better supported in Haskell, it sounds like you could live with process level parallelism (from your phrase: ideally separating out each execution to run in parallel.) which is supported quite well in OCaml. Keith pointed out that Haskell has a more powerful type system, but it can also be said that OCaml has a more powerful module system than Haskell.
As others have pointed out, OCaml's learning curve will be lower than Haskell's; you'll likely be more productive more quickly in OCaml. That said, learning OCaml is a great stepping-stone towards learning Haskell because many of the underlying concepts are very similar, so you could always migrate to Haskell later and find a lot of things familiar there. And as you pointed out, there is an OCaml-R bridge.
As an examples of Haskell and Ocaml in machine learning see stuff at Hal Daume and Lloyd Allison homepages. IMO it's is much more straightforward to achieve C++-like performance in Ocaml, than in Haskell. Through, as already said, Haskell has much nicer community (packages, tools and support), syntax&features (i.e. FFI, probability monads via typeclasses) and parallel programming support.
Having revamped OCaml-R, I've got a few comments to make on integrating OCaml and R. It might be worthwile to use OCaml to call R code, it works, but is not yet exactly straightforward. So using it to pilot R is worthwile. Integrating R functionality much more thoroughly is still cumbersome as, for example, much remains to be done to export R's type system and data to OCaml in a seamless way (you will have work to do). Moreover, the interaction of R's GC and OCaml's GC is a delicate point: you free n values in O(n^2) time, which isn't nice (to solve this point, you either need a more flexible R API, as far as I understand it, or to implement a GC in the binding itself as a big R array for proper interaction between GCs).
In a nutshell, I'd go for the "pilot R from OCaml" approach.
Contributions on the GC interaction layer and on mapping R datatypes to OCaml are most welcome.
You may want to take a look at this : http://www.haskell.org/pipermail/haskell-cafe/2010-May/077243.html
Late answer but a machine learning library in Haskell is available here : https://github.com/mikeizbicki/HLearn
This library implements various ML algorithms who are designed to have a much faster cross-validation than the usual implementations. It is based on the following paper Algebraic classifiers: a generic approach to fast cross-validation,
online training, and parallel training. The authors claims a 400x speed-up compared to the same task in Weka.
for haskell, consider checking hasktorch (which I managed to use for my AI thesis). for ocaml there seem to be tensorflow bindings.

What do I learn to "enlighten myself with the ways" of functional programming?

I've been coding for a few years now, nothing too complicated. C++ is what I know best. I recently stumbled into Paul Graham's site, coding horror, and now here.
What do I learn to "enlighten myself with the ways" of functional programming? Haskell, Scheme or CLisp?
If you're interested in functional programming, Haskell is the only purely functional language on that list. Common Lisp is a weakly functional mixed-paradigm language, and Scheme is more strongly functional but still not pure. Lisps are interesting for other reasons, but Haskell is pretty much the state of the art for functional programming.
Incidentally, the reason I encourage more strongly functional languages like Haskell is because a large part of "learning functional programming" is learning how to think of your program in a different way. If your language makes it feel natural to write imperatively, it's too easy to fall into that way of thinking and never realize there's a different way to do it.
Of the three, I'd say Scheme is the simplest overall, if that's your main concern. SICP uses Scheme, and is itself a great resource for learning to program the functional way.
However, Common Lisp has many advanced features that make it quite expressive, such as powerful error handling (more powerful than exceptions), multimethods and support for aspect oriented programming.
You might start with one but, in the end, you should study many languages.
All three are good, depends on each person.
If you decide on haskell, this is a great ressource : learnyouahaskell and also real world haskell
As other answers say, all three are good.
But if you decide on Lisp, then I'd suggest you go for Clojure which is perhaps its most recent reincarnation.
'enlighten myself with the ways' of functional programming?
Haskell's the strongest exemplar of the functional style, emphasizing purely functional programming (no side effects), strong static typing, and with a pragmatic implementation with an emphasis on multicore parallelism, while also having a huge community (around 2000 libraries available on http://hackage.haskell.org , and many online resources).
It's somewhat famous for retraining how people think about programming.
But this is advocacy, and not a useful stackoverflow question and answer session. You'll have to decide for yourself what you're looking to learn.
Have you heard of F#, ML or OCaml? These three languages belong to the ML family.
F# is a new ML dialect supported by Microsoft and will be shipped with Visual Studio 2010. The good thing about F# (or other ML languages) is that when you first start you could write imperative code and learn good functional style gradually.
Here's an example I wrote for Project Euler #2. When I first did it, I used imperative style. Later on, I know how to use lazy sequence, which is a powerful functional programming concept.

Getting started with Haskell

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For a few days I've tried to wrap my head around the functional programming paradigm in Haskell. I've done this by reading tutorials and watching screencasts, but nothing really seems to stick.
Now, in learning various imperative/OO languages (like C, Java, PHP), exercises have been a good way for me to go. But since I don't really know what Haskell is capable of and because there are many new concepts to utilize, I haven't known where to start.
So, how did you learn Haskell? What made you really "break the ice"? Also, any good ideas for beginning exercises?
I'm going to order this guide by the level of skill you have in Haskell, going from an absolute beginner right up to an expert. Note that this process will take many months (years?), so it is rather long.
Absolute Beginner
Firstly, Haskell is capable of anything, with enough skill. It is very fast (behind only C and C++ in my experience), and can be used for anything from simulations to servers, guis and web applications.
However there are some problems that are easier to write for a beginner in Haskell than others. Mathematical problems and list process programs are good candidates for this, as they only require the most basic of Haskell knowledge to be able to write.
Some good guides to learning the very basics of Haskell are the Happy Learn Haskell Tutorial and the first 6 chapters of Learn You a Haskell for Great Good (or its JupyterLab adaptation). While reading these, it is a very good idea to also be solving simple problems with what you know.
Another two good resources are Haskell Programming from first principles, and Programming in Haskell. They both come with exercises for each chapter, so you have small simple problems matching what you learned on the last few pages.
A good list of problems to try is the haskell 99 problems page. These start off very basic, and get more difficult as you go on. It is very good practice doing a lot of those, as they let you practice your skills in recursion and higher order functions. I would recommend skipping any problems that require randomness as that is a bit more difficult in Haskell. Check this SO question in case you want to test your solutions with QuickCheck (see Intermediate below).
Once you have done a few of those, you could move on to doing a few of the Project Euler problems. These are sorted by how many people have completed them, which is a fairly good indication of difficulty. These test your logic and Haskell more than the previous problems, but you should still be able to do the first few. A big advantage Haskell has with these problems is Integers aren't limited in size. To complete some of these problems, it will be useful to have read chapters 7 and 8 of learn you a Haskell as well.
Beginner
After that you should have a fairly good handle on recursion and higher order functions, so it would be a good time to start doing some more real world problems. A very good place to start is Real World Haskell (online book, you can also purchase a hard copy). I found the first few chapters introduced too much too quickly for someone who has never done functional programming/used recursion before. However with the practice you would have had from doing the previous problems you should find it perfectly understandable.
Working through the problems in the book is a great way of learning how to manage abstractions and building reusable components in Haskell. This is vital for people used to object-orientated (oo) programming, as the normal oo abstraction methods (oo classes) don't appear in Haskell (Haskell has type classes, but they are very different to oo classes, more like oo interfaces). I don't think it is a good idea to skip chapters, as each introduces a lot new ideas that are used in later chapters.
After a while you will get to chapter 14, the dreaded monads chapter (dum dum dummmm). Almost everyone who learns Haskell has trouble understanding monads, due to how abstract the concept is. I can't think of any concept in another language that is as abstract as monads are in functional programming. Monads allows many ideas (such as IO operations, computations that might fail, parsing,...) to be unified under one idea. So don't feel discouraged if after reading the monads chapter you don't really understand them. I found it useful to read many different explanations of monads; each one gives a new perspective on the problem. Here is a very good list of monad tutorials. I highly recommend the All About Monads, but the others are also good.
Also, it takes a while for the concepts to truly sink in. This comes through use, but also through time. I find that sometimes sleeping on a problem helps more than anything else! Eventually, the idea will click, and you will wonder why you struggled to understand a concept that in reality is incredibly simple. It is awesome when this happens, and when it does, you might find Haskell to be your favorite imperative programming language :)
To make sure that you are understanding Haskell type system perfectly, you should try to solve 20 intermediate haskell exercises. Those exercises using fun names of functions like "furry" and "banana" and helps you to have a good understanding of some basic functional programming concepts if you don't have them already. Nice way to spend your evening with a bunch of papers covered with arrows, unicorns, sausages and furry bananas.
Intermediate
Once you understand Monads, I think you have made the transition from a beginner Haskell programmer to an intermediate haskeller. So where to go from here? The first thing I would recommend (if you haven't already learnt them from learning monads) is the various types of monads, such as Reader, Writer and State. Again, Real world Haskell and All about monads gives great coverage of this. To complete your monad training learning about monad transformers is a must. These let you combine different types of Monads (such as a Reader and State monad) into one. This may seem useless to begin with, but after using them for a while you will wonder how you lived without them.
Now you can finish the real world Haskell book if you want. Skipping chapters now doesn't really matter, as long as you have monads down pat. Just choose what you are interested in.
With the knowledge you would have now, you should be able to use most of the packages on cabal (well the documented ones at least...), as well as most of the libraries that come with Haskell. A list of interesting libraries to try would be:
Parsec: for parsing programs and text. Much better than using regexps. Excellent documentation, also has a real world Haskell chapter.
QuickCheck: A very cool testing program. What you do is write a predicate that should always be true (eg length (reverse lst) == length lst). You then pass the predicate the QuickCheck, and it will generate a lot of random values (in this case lists) and test that the predicate is true for all results. See also the online manual.
HUnit: Unit testing in Haskell.
gtk2hs: The most popular gui framework for Haskell, lets you write gtk applications.
happstack: A web development framework for Haskell. Doesn't use databases, instead a data type store. Pretty good docs (other popular frameworks would be snap and yesod).
Also, there are many concepts (like the Monad concept) that you should eventually learn. This will be easier than learning Monads the first time, as your brain will be used to dealing with the level of abstraction involved. A very good overview for learning about these high level concepts and how they fit together is the Typeclassopedia.
Applicative: An interface like Monads, but less powerful. Every Monad is Applicative, but not vice versa. This is useful as there are some types that are Applicative but are not Monads. Also, code written using the Applicative functions is often more composable than writing the equivalent code using the Monad functions. See Functors, Applicative Functors and Monoids from the learn you a haskell guide.
Foldable,Traversable: Typeclasses that abstract many of the operations of lists, so that the same functions can be applied to other container types. See also the haskell wiki explanation.
Monoid: A Monoid is a type that has a zero (or mempty) value, and an operation, notated <> that joins two Monoids together, such that x <> mempty = mempty <> x = x and x <> (y <> z) = (x <> y) <> z. These are called identity and associativity laws. Many types are Monoids, such as numbers, with mempty = 0 and <> = +. This is useful in many situations.
Arrows: Arrows are a way of representing computations that take an input and return an output. A function is the most basic type of arrow, but there are many other types. The library also has many very useful functions for manipulating arrows - they are very useful even if only used with plain old Haskell functions.
Arrays: the various mutable/immutable arrays in Haskell.
ST Monad: lets you write code with a mutable state that runs very quickly, while still remaining pure outside the monad. See the link for more details.
FRP: Functional Reactive Programming, a new, experimental way of writing code that handles events, triggers, inputs and outputs (such as a gui). I don't know much about this though. Paul Hudak's talk about yampa is a good start.
There are a lot of new language features you should have a look at. I'll just list them, you can find lots of info about them from google, the haskell wikibook, the haskellwiki.org site and ghc documentation.
Multiparameter type classes/functional dependencies
Type families
Existentially quantified types
Phantom types
GADTS
others...
A lot of Haskell is based around category theory, so you may want to look into that. A good starting point is Category Theory for Computer Scientist. If you don't want to buy the book, the author's related article is also excellent.
Finally you will want to learn more about the various Haskell tools. These include:
ghc (and all its features)
cabal: the Haskell package system
darcs: a distributed version control system written in Haskell, very popular for Haskell programs.
haddock: a Haskell automatic documentation generator
While learning all these new libraries and concepts, it is very useful to be writing a moderate-sized project in Haskell. It can be anything (e.g. a small game, data analyser, website, compiler). Working on this will allow you to apply many of the things you are now learning. You stay at this level for ages (this is where I'm at).
Expert
It will take you years to get to this stage (hello from 2009!), but from here I'm guessing you start writing phd papers, new ghc extensions, and coming up with new abstractions.
Getting Help
Finally, while at any stage of learning, there are multiple places for getting information. These are:
the #haskell irc channel
the mailing lists. These are worth signing up for just to read the discussions that take place - some are very interesting.
other places listed on the haskell.org home page
Conclusion
Well this turned out longer than I expected... Anyway, I think it is a very good idea to become proficient in Haskell. It takes a long time, but that is mainly because you are learning a completely new way of thinking by doing so. It is not like learning Ruby after learning Java, but like learning Java after learning C. Also, I am finding that my object-orientated programming skills have improved as a result of learning Haskell, as I am seeing many new ways of abstracting ideas.
Some colleague of mine had good experience with Learn You a Haskell for Great Good!.
Tutorial aimed at people who have
experience in imperative programming
languages but haven't programmed in a
functional language before.
And check the answers here too
Here's a good book that you can read online: Real World Haskell
Most of the Haskell programs I've done have been to solve Project Euler problems.
Once piece of advice I read not too long ago was that you should have a standard set of simple problems you know how to solve (in theory) and then whenever you try to learn a new language you implement those problems in that language.
I enjoyed watching this 13 episode series on Functional Programming using Haskell.
C9 Lectures: Dr. Erik Meijer - Functional Programming Fundamentals:
http://channel9.msdn.com/shows/Going+Deep/Lecture-Series-Erik-Meijer-Functional-Programming-Fundamentals-Chapter-1/
To add on others' answers - there is one useful that will help you when coding (for example when solving project Euler problems):
Hoogle. You can use either the command line interface or the web interface.
Command Line
After you installed the Haskell platform be sure to cabal install hoogle
Hoogle usage example:
You have a function f x = 3 * x + 1 and you want to apply it on (5 :: Int), then apply it on the result and on that result and so on and get an infinite list of those values. You suspect there might already exist a function to assist you (not specifically for your f though).
That function would be of type (a -> a) -> a -> [a] if it takes f 5 or a -> (a -> a) -> [a] if it takes 5 f (we assume the function is for general types and not just Ints)
$ hoogle "a -> (a -> a) -> [a]"
Prelude iterate :: (a -> a) -> a -> [a]
yep, the function you need already exists and it's called iterate. you use it by iterate func 5!
Web interface
The result for the same example can be found here.
Graham Hutton's Programming in Haskell is concise, reasonably thorough, and his years of teaching Haskell really show. It's almost always what I recommend people start with, regardless of where you go from there.
In particular, Chapter 8 ("Functional Parsers") provides the real groundwork you need to start dealing with monads, and I think is by far the best place to start, followed by All About Monads. (With regard to that chapter, though, do note the errata from the web site, however: you can't use the do form without some special help. You might want to learn about typeclasses first and solve that problem on your own.)
This is rarely emphasized to Haskell beginners, but it's worth learning fairly early on not just about using monads, but about constructing your own. It's not hard, and customized ones can make a number of tasks rather more simple.
Don't try to read all the monad tutorials with funny metaphors. They will just get you mixed up even worse.
I'd suggest joining the #haskell irc channel and asking questions there. That's how I learned Haskell. If you go through Real World Haskell as suggested above, real time answers to your questions will help greatly. Lots of smart people on #haskell write Haskell for fun and for profit, so you'll get lots of good input. Try it!
These are my favorite
Haskell: Functional Programming with Types
Joeri van Eekelen, et al. | Wikibooks
Published in 2012, 597 pages
Real World Haskell
B. O'Sullivan, J. Goerzen, D. Stewart | OReilly Media, Inc.
Published in 2008, 710 pages
I can additionally recommend Yet Another Haskell Tutorial as an introduction.
Another good learning resource (probably on the intermediate level), which has helped me a lot and hasn't been mentioned in the other answers as far as I can see, is Brent Yorgey's Typeclassopedia, which can be found in The Monad Reader (Issue 13)
It is written in a very accessible style and contains (among many other things), the following introductory advice:
There are two keys to an expert Haskell hacker’s wisdom:
Understand the types.
Gain a deep intuition for each type class and its relationship to other
type classes, backed up by familiarity with many examples.
The Monad Reader itself is an absolute treasure trove for functional programmers (not only Haskell programmers).
Try writing easy programs in it.
You can find sample tasks in various textbooks, probably.
I wouldn't recommend sticking to Haskell/FP textbooks, just try to do simple things with it: calculations, string manipulations, file access.
After I solved a dozen, I've broke the ice :)
After that, read a lot on advanced concepts (Monads, Arrows, IO, recursive data structures), because haskell is infinite and there are a lot of them.
I do think that realizing Haskell's feature by examples is the best way to start above all.
http://en.wikipedia.org/wiki/Haskell_98_features
Here is tricky typeclasses including monads and arrows
http://www.haskell.org/haskellwiki/Typeclassopedia
for real world problems and bigger project, remember these tags: GHC(most used compiler), Hackage(libraryDB), Cabal(building system), darcs(another building system).
A integrated system can save your time: http://hackage.haskell.org/platform/
the package database for this system: http://hackage.haskell.org/
GHC compiler's wiki: http://www.haskell.org/haskellwiki/GHC
After Haskell_98_features and Typeclassopedia, I think you already can find and read the documention about them yourself
By the way, you may want to test some GHC's languages extension which may be a part of haskell standard in the future.
this is my best way for learning haskell. i hope it can help you.
I suggest that you first start by reading BONUS' tutorial, And then reading Real World Haskell (online for free). Join the #Haskell IRC channel, on irc.freenode.com, and ask questions. These people are absolutely newbie friendly, and have helped me a lot over time. Also, right here on SO is a great place to get help with things you can't grasp! Try not to get discouraged, once it clicks, your mind will be blown.
BONUS' tutorial will prime you up, and get you ready for the thrill ride that Real World Haskell brings. I wish you luck!
If you only have experience with imperative/OO languages, I suggest using a more conventional functional language as a stepping stone. Haskell is really different and you have to understand a lot of different concepts to get anywhere. I suggest tackling a ML-style language (like e.g. F#) first.
The first answer is a very good one. In order to get to the Expert level, you should do a PhD with some of the Experts themselves.
I suggest you to visit the Haskell page: http://haskell.org. There you have a lot of material, and a lot of references to the most up-to-date stuff in Haskell, approved by the Haskell community.

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