Closed. This question needs to be more focused. It is not currently accepting answers.
Want to improve this question? Update the question so it focuses on one problem only by editing this post.
Closed 8 years ago.
Improve this question
I'm currently working on a recommendation system that uses collaborative filtering. And now I'm researching for a good/efficient algorithm that is geared towards movie recommendation. I'm confused because there are many algorithm like the Pearson Correlation Coefficient. And so I don't know what to use/implement.
Can you give me a good/efficient algorithm? or a site that gives a good example or simulation to the algorithm?
Thanks for the help!
Give this paper about the netflix prize a read Netflix Prize. Usually the 'state of the art' is some variant of matrix factorisation such as OrdRec. Check out the Funk Blog FunkSVD which will give you a nice simple explanation about implementing the starts of a matrix factorization technique for CF.
Matrix factorisation (An example in Python) is a good starting point. Furthermore, I'd recommend Ed Chen's Blog and The Mining of Massive Datasets as good introductions to the variety of methods used to solve this type of problem. The interesting thing for me having worked with this type of data is the amount of sparseness, there are of course practical limits, papers by Emmanual Candes seem to shed light on this area, excellent advanced work.
Related
Closed. This question needs to be more focused. It is not currently accepting answers.
Want to improve this question? Update the question so it focuses on one problem only by editing this post.
Closed 7 years ago.
Improve this question
I am a novice to algorithms and data structures. I recently started participating on codeforces and spoj etc.for solving questions i need to study dp,greedy algorithms,graph algorithms,data structures.what should be my strategy for studying or rather sequence and what data structures i need to know for competitive programming?
All in all there shouldnt be an "optimal" sequence. Its all about understanding the topic. Since not two people can learn with the same speed, there shouldnt be something like an "optimal" sequence. But its good to learn basic approaches of each topic.
There are alot Tutorials out there, which explains the most fundamental thing in any topic. E.g. Youtube covers most graph problems. Even DP and so can be found there. Especially on Topcoder Tutorials there is alot you can learn.
On the other hand you will learn nearly nothing, if u dont have to think for yourself. So solving such puzzles is a must. I would recommend this site (especially for dp). Just check the "problem set" link on the site and look for dynamic programming.
I recommend you this book: Competitive Progamming, by Halim. Is very complete, and newbie-compatible.
Closed. This question is opinion-based. It is not currently accepting answers.
Want to improve this question? Update the question so it can be answered with facts and citations by editing this post.
Closed 9 years ago.
Improve this question
I want to improve my programming skills, when I participate in some programming competition I feel that every challenge is so tough that i can not solve it,I have good knowledge of coding but I fell to decide the algorithm needed to solve particular problem for that can anyone tell me which books to read
I would suggest first to get comfortable with programming language of your choice. Once you have confidence on your language and Data structure, you can proceed confidently for any programming challenges. Make a habit of writing complete code with all edge cases handled on a sheet of paper rather than simple pseudo code for your practice session.
Now to solve algorithmic problem first to grasp elementary algo functioning via book or online resources. If you are using coreman (good book for algo) then you might want to understand basic concepts of different sorting techniques, heap, queue, hashing, greedy and dynamic algorithm. For some topic i would recommend to research online as well - like dynamic programming and hashing. Almost 70-80% interview questions are either hashing or DP based. Then look for major examples and their solution for these algorithm. Once your mind will set up you would be able to think quickly for any algorithmic problem.
Introduction to Algorithms by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest , Clifford Stein is a good one to start with.
Covers almost everything, from graph theory to geometric algorithms and all related data structures, furthermore they use the commonly used "Big O" notation to indicate the efficiency of the algorithms explained. Most of the time multiple algorithms are presented for the same problem, together with their advantages and disadvantages.
Closed. This question is off-topic. It is not currently accepting answers.
Want to improve this question? Update the question so it's on-topic for Stack Overflow.
Closed 9 years ago.
Improve this question
There are many Online Judges (OJ) for ACM/ICPC questions. And another Online Judge for Interview questions, named Leetcode (http://leetcode.com).
I think these OJs are very useful for us to learn algorithms. Recently, I am going to learn data mining algorithms. Is there any OJ for data mining questions?
Thank you very much.
There is MLcomp, where you can submit an algorithm and it will run it on a number of data sets to judge how well it is doing.
Plus, there is Kaggle, which hosts various classification competitions.
And of course you can do classes at Cousera. These are pretty much low level, but in order to get submission points you need to reproduce the known performance.
In particular the first also allows you to run several standard algorithms such as naive bayes and SVM and see how well they did. Obviously, your own implementation should perform similar then.
Unfortunately, both are pretty much focused on machine learning (i.e. classification and regression). There is very little in the unsupervised domain, clustering and outlier detection. On unlabeled data, things get too hard even to evaluate locally, so doing any kind of online judging is pretty much unsolved. What you can do is largely a one-class classification, or you just strip labels before running the algorithm.
Closed. This question is off-topic. It is not currently accepting answers.
Want to improve this question? Update the question so it's on-topic for Stack Overflow.
Closed 10 years ago.
Improve this question
I'm good at algorithms but not as good as converting real-time problems and learning them throughly to make it as an algorithm. I would like to know if there is any book/paper that teaches or makes you demystify the situation and formulate it as an algorithm. (Its much like training your mental ability to break the situation and comeup with algorithm in a crisp.)
Showing some of the ways to approach these kinda problems. and any easy learning links/material would help me a lot.
Note: I know SO doesnt allow to ask for the opinion or something vague (I dont mind my Q being downgraded). But I am asking some concrete problem and hope can get some nice info from some of the great minds here.
The word that fits better as a direct answer is "experience". There exists no magical formula to convert a real time problem into some algorithms that solve it. As an analogy, there exist no predefined patterns on how to solve a mathematical problem. It is a mind's task to express the solution, based on some fundamental knowledge and on experience that is accumulated though constant learning.
Closed. This question is opinion-based. It is not currently accepting answers.
Want to improve this question? Update the question so it can be answered with facts and citations by editing this post.
Closed 5 years ago.
Improve this question
I came across the declaration in a software best practices guide that algorithm and code shouldn't get mixed up. I'm not sure what is meant by this? As far as I understand, code is the implementation of the algorithm, isn't is? So, what exactly is meant by this statement? and why it is considered as a good practice?
Thank You!
The context in which the author mentioned would be clearer if you had pasted the surrounding lines.
Though what it would mean to me is, an algorithm is just a clear step-by-step logic that you would use to implement. You would leave out the finer implementation details like selection of the right data structure and other implementation details while you write/design the algorithm.
A good explanation can be found here
An algorithm is a series of steps for solving a problem, completing a task or performing a calculation. Algorithms are usually executed by computer programs but the term can also apply to steps in domains such as mathematics for human problem solving.
Code is a series of steps that machines can execute. In many cases, code is composed in a high level language that is then automatically translated into instructions that machines understand.