xgboost
mlpack
Our great sponsors
xgboost | mlpack | |
---|---|---|
10 | 4 | |
25,528 | 4,787 | |
0.8% | 2.0% | |
9.7 | 9.9 | |
6 days ago | 3 days ago | |
C++ | C++ | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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.
xgboost
-
PSA: You don't need fancy stuff to do good work.
Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive documentation and community support, making it easy to learn and apply new techniques without needing specialized training or expensive software licenses.
-
xgboost VS CXXGraph - a user suggested alternative
2 projects | 28 Feb 2022
mlpack
-
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.
-
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.
-
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
What are some alternatives?
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
MLP Classifier - A handwritten multilayer perceptron classifer using numpy.
tensorflow - An Open Source Machine Learning Framework for Everyone
Keras - Deep Learning for humans
Dlib - A toolkit for making real world machine learning and data analysis applications in C++
SHOGUN - ShÅgun
Caffe - Caffe: a fast open framework for deep learning.
catboost - A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.
scikit-learn - scikit-learn: machine learning in Python
mxnet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more