awesome-theoretical-computer VS SHOGUN

Compare awesome-theoretical-computer vs SHOGUN and see what are their differences.

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awesome-theoretical-computer SHOGUN
1 1
- 3,005
- 0.2%
- 4.8
- 4 months ago
C++
- BSD 3-clause "New" or "Revised" License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

awesome-theoretical-computer

Posts with mentions or reviews of awesome-theoretical-computer. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-04-20.

SHOGUN

Posts with mentions or reviews of SHOGUN. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-04-20.
  • Changing std:sort at Google’s Scale and Beyond
    7 projects | news.ycombinator.com | 20 Apr 2022
    The function is trying to get the median, which is not defined for an empty set. With this particular implementation, there is an assert for that:

    https://github.com/shogun-toolbox/shogun/blob/9b8d85/src/sho...

    Unrelatedly, but from the same section:

    > Fixes are trivial, access the nth element only after the call being made. Be careful.

    Wouldn't the proper fix to do the nth_element for the larget element first (for those cases that don't do that already) and then adjust the end to be the begin + larger_n for the second nth_element call? Otherwise the second call will check [begin + larger_n, end) again for no reason at all.

What are some alternatives?

When comparing awesome-theoretical-computer and SHOGUN you can also consider the following projects:

crumsort - A branchless unstable quicksort / mergesort that is highly adaptive.

mlpack - mlpack: a fast, header-only C++ machine learning library

awesome-theoretical-computer-science - The interdicplinary of Mathematics and Computer Science, Distinguisehed by its emphasis on mathemtical technique and rigour.

Caffe - Caffe: a fast open framework for deep learning.

fluxsort - A fast branchless stable quicksort / mergesort hybrid that is highly adaptive.

mxnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

xeus-cling - Jupyter kernel for the C++ programming language

Dlib - A toolkit for making real world machine learning and data analysis applications in C++

awesome-algorithms - A curated list of awesome places to learn and/or practice algorithms.

vowpal_wabbit - Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.

xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

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