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  2. Project Euler - Wikipedia

    en.wikipedia.org/wiki/Project_Euler

    Find the sum of all the multiples of 3 or 5 below 1000. It is a 5% rated problem, indicating it is one of the easiest on the site. The initial approach a beginner can come up with is a bruteforce attempt. Given the upper bound of 1000 in this case, a bruteforce is easily achievable for most current home computers.

  3. Monty Hall problem - Wikipedia

    en.wikipedia.org/wiki/Monty_Hall_problem

    After the problem appeared in Parade, approximately 10,000 readers, including nearly 1,000 with PhDs, wrote to the magazine, most of them calling Savant wrong. [4] Even when given explanations, simulations, and formal mathematical proofs, many people still did not accept that switching is the best strategy. [ 5 ]

  4. User:Smallbones/1000 random results - Wikipedia

    en.wikipedia.org/wiki/User:Smallbones/1000...

    These and similar questions are examined using 1001 random articles sampled in December, 2015. The 18 categories and subcategories are dominated by biographies (27.8% of all articles), with biographies of men (23.8%) being 5.8 times as common as women (4.1%).

  5. Collatz conjecture - Wikipedia

    en.wikipedia.org/wiki/Collatz_conjecture

    less than 1000 is 871, which has 178 steps, less than 10 4 is 6171, which has 261 steps, less than 10 5 is 77 031, which has 350 steps, less than 10 6 is 837 799, which has 524 steps, less than 10 7 is 8 400 511, which has 685 steps, less than 10 8 is 63 728 127, which has 949 steps, less than 10 9 is 670 617 279, which has 986 steps,

  6. Okapi BM25 - Wikipedia

    en.wikipedia.org/wiki/Okapi_BM25

    In information retrieval, Okapi BM25 (BM is an abbreviation of best matching) is a ranking function used by search engines to estimate the relevance of documents to a given search query.

  7. CuPy - Wikipedia

    en.wikipedia.org/wiki/CuPy

    CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. [3] CuPy shares the same API set as NumPy and SciPy, allowing it to be a drop-in replacement to run NumPy/SciPy code on GPU.

  8. GSP algorithm - Wikipedia

    en.wikipedia.org/wiki/GSP_Algorithm

    F 1 = the set of frequent 1-sequence k=2, do while F k-1 != Null; Generate candidate sets C k (set of candidate k-sequences); For all input sequences s in the database D do Increment count of all a in C k if s supports a End do Fk = {a ∈ C k such that its frequency exceeds the threshold} k = k+1; End do Result = Set of all frequent sequences is the union of all F k 's

  9. History of Python - Wikipedia

    en.wikipedia.org/wiki/History_of_Python

    Python 2.6 was released to coincide with Python 3.0, and included some features from that release, as well as a "warnings" mode that highlighted the use of features that were removed in Python 3.0. [ 28 ] [ 10 ] Similarly, Python 2.7 coincided with and included features from Python 3.1, [ 29 ] which was released on June 26, 2009.