mlpack
SHOGUN
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mlpack | SHOGUN | |
---|---|---|
4 | 1 | |
4,742 | 2,997 | |
1.6% | 0.4% | |
9.9 | 4.8 | |
3 days ago | 3 months ago | |
C++ | C++ | |
GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
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.
mlpack
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What is the most used library for AI in C++ ?
mlpack is a great library for machine learning in C++. It's very fast and not too much of a learning curve.
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Ensmallen: A C++ Library for Efficient Numerical Optimization
This toolkit was originally part of the mlpack machine learning library (https://github.com/mlpack/mlpack) before it was split out into a separate, standalone effort.
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Top 10 Python Libraries for Machine Learning
Github Repository: https://github.com/mlpack/mlpack Developed By: Community, supported by Georgia Institute of technology Primary purpose: Multiple ML Models and Algorithms
SHOGUN
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Changing std:sort at Google’s Scale and Beyond
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?
tensorflow - An Open Source Machine Learning Framework for Everyone
Dlib - A toolkit for making real world machine learning and data analysis applications in C++
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
Caffe - Caffe: a fast open framework for deep learning.
mxnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
examples - TensorFlow examples
NN++ - A small and easy to use neural net implementation for C++. Just download and #include!
RNNLIB - RNNLIB is a recurrent neural network library for sequence learning problems. Forked from Alex Graves work http://sourceforge.net/projects/rnnl/