Contents

mlpack 4.5.0

0

a flexible, fast machine learning library

a flexible, fast machine learning library

Stars: 5062, Watchers: 5062, Forks: 1602, Open Issues: 23

The mlpack/mlpack repo was created 9 years ago and the last code push was Yesterday.
The project is extremely popular with a mindblowing 5062 github stars!

How to Install mlpack

You can install mlpack using pip

pip install mlpack

or add it to a project with poetry

poetry add mlpack

Package Details

Author
mlpack developers
License
BSD
Homepage
http://www.mlpack.org/
PyPi:
https://pypi.org/project/mlpack/
Documentation:
http://www.mlpack.org/doc/mlpack-4.5.0/python.html
GitHub Repo:
https://github.com/mlpack/mlpack

Classifiers

  • Scientific/Engineering/Artificial Intelligence
  • Scientific/Engineering/Mathematics
  • Software Development/Libraries
  • Software Development/Libraries/Application Frameworks
No  mlpack  pypi packages just yet.

Errors

A list of common mlpack errors.

Code Examples

Here are some mlpack code examples and snippets.

GitHub Issues

The mlpack package has 23 open issues on GitHub

  • added check for input data value
  • getting all class prediction with probability score for classification model like random forest
  • Added Simple Exponential Smoothing model for time series
  • adding sample examples for adaptive layers
  • Instance Norm
  • Subset Selection on data
  • Removing Remaining Boost
  • Added checks for relative input shapes in linear regression and k means clustering
  • move and copy constructor for pooling layers
  • input_labels parameter in preprocess_split function can't be empty
  • Randomized ReLU Activation Function
  • LayerNorm copy and move constructor created
  • Implementation of Threshold Activation Fn Done
  • A loaded model with PReLU does not produce expected predictions
  • add implementation of ISRU activation function

See more issues on GitHub

Related Packages & Articles

dlib 19.24.6

A toolkit for making real world machine learning and data analysis applications

mediapipe 0.10.15

MediaPipe is the simplest way for researchers and developers to build world-class ML solutions and applications for mobile, edge, cloud and the web.

thinc 9.1.1

A refreshing functional take on deep learning, compatible with your favorite libraries

pyro-ppl 1.9.1

A Python library for probabilistic modeling and inference

orbit-ml 1.1.4.9

Orbit is a package for Bayesian time series modeling and inference.

fiftyone 1.0.0

FiftyOne: the open-source tool for building high-quality datasets and computer vision models

gradio 5.0.2

Python library for easily interacting with trained machine learning models