10

8

6

4

2


10.0

10.0
tensorflow

9.9

9.9
scikit-learn

9.9

9.7
Keras

9.8

9.5
xgboost

9.8

9.2
gym

9.6
0.0
CNTK

45 Machine Learning packages and projects

  • tensorflow

    10.0 10.0 L1 C++
    An Open Source Machine Learning Framework for Everyone

  • scikit-learn

    9.9 9.9 L3 Python
    scikit-learn: machine learning in Python

    • Scout APM uses tracing logic that ties bottlenecks to source code so you know the exact line of code causing performance issues and can get back to building a great product faster.
    Promo

  • Keras

    9.9 9.7 L2 Python
    Deep Learning for humans

  • xgboost

    9.8 9.5 L1 C++
    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

  • gym

    9.8 9.2 Python
    A toolkit for developing and comparing reinforcement learning algorithms.

  • CNTK

    9.6 0.0 L1 C++
    Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit

  • PaddlePaddle

    9.6 10.0 L1 Python
    PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）

  • gensim

    9.5 8.9 L3 Python
    Topic Modelling for Humans

  • Prophet

    9.5 7.9 Python
    Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

  • MLflow

    9.3 9.7 Python
    Open source platform for the machine learning lifecycle

  • TFLearn

    9.3 1.8 L3 Python
    Deep learning library featuring a higher-level API for TensorFlow.

  • NuPIC

    9.0 0.0 L3 Python
    Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of intelligence based strictly on the neuroscience of the neocortex.

  • H2O

    8.9 9.9 Jupyter Notebook
    H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

  • Surprise

    8.4 0.0 L4 Python
    A Python scikit for building and analyzing recommender systems

  • srez

    8.4 0.0 L5 Python
    Image super-resolution through deep learning

  • Pylearn2

    8.1 0.0 L2 Python
    Warning: This project does not have any current developer. See bellow.

  • PyBrain

    7.9 0.0 L4 Python
    Another Python Machine Learning Library.

  • MindsDB

    7.9 9.9 Python
    Predictive AI layer for existing databases.

  • LightFM

    7.9 4.8 L4 Python
    A Python implementation of LightFM, a hybrid recommendation algorithm.

  • skflow

    7.7 0.0 L4 Python
    Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning

  • Sacred

    7.6 5.5 Python
    Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.

  • Clairvoyant

    7.4 1.0 L3 Python
    Software designed to identify and monitor social/historical cues for short term stock movement

  • Metrics

    6.4 0.0 Python
    Machine learning evaluation metrics, implemented in Python, R, Haskell, and MATLAB / Octave

  • python-recsys

    6.4 0.0 L4 Python
    A python library for implementing a recommender system

  • pydeep

    6.2 0.0 L3 Python
    Deep learning in Python

  • awesome-embedding-models

    6.1 0.0 Jupyter Notebook
    A curated list of awesome embedding models tutorials, projects and communities.

  • Crab

    5.9 0.0 L2 Python
    Crab is a flexible, fast recommender engine for Python that integrates classic information filtering recommendation algorithms in the world of scientific Python packages (numpy, scipy, matplotlib).

  • karateclub

    5.5 8.3 Python
    Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

  • hebel

    5.3 0.0 L2 Python
    GPU-Accelerated Deep Learning Library in Python

  • seqeval

    4.0 4.1 Python
    A Python framework for sequence labeling evaluation(named-entity recognition, pos tagging, etc...)

  • adaptive

    3.9 8.0 Python
    :chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions

  • SciKit-Learn Laboratory

    3.9 8.4 Python
    SciKit-Learn Laboratory (SKLL) makes it easy to run machine learning experiments.

  • rwa

    3.9 0.0 L5 Python
    Machine Learning on Sequential Data Using a Recurrent Weighted Average

  • pdpipe

    3.7 3.7 Python
    Easy pipelines for pandas DataFrames.

  • Feature Forge

    3.5 0.0 L4 Python
    A set of tools for creating and testing machine learning features, with a scikit-learn compatible API

  • brew

    3.2 0.0 L4 Python
    Multiple Classifier Systems and Ensemble Learning Library in Python.

  • Data Flow Facilitator for Machine Learning (dffml)

    2.9 9.7 Python
    The easiest way to use Machine Learning. Mix and match underlying ML libraries and data set sources. Generate new datasets or modify existing ones with ease.

  • MLP Classifier

    2.7 0.0 L4 Python
    A handwritten multilayer perceptron classifer using numpy.

  • bodywork

    2.7 9.5 Python
    ML pipeline orchestration and model deployments on Kubernetes, made really easy.

  • vowpal_porpoise

    2.5 0.0 L3 Python
    lightweight python wrapper for vowpal wabbit

  • nptyping

    2.5 6.5 Python
    💡 Type hints for Numpy

  • tfgraphviz

    1.3 3.0 L5 Python
    A visualization tool to show a TensorFlow's graph like TensorBoard

  • neptune-contrib

    1.3 4.1 Python
    Tools, helpers and everything else that helps you work with Neptune.

  • Simple GAN

    0.6 0.0 Python
    Attempt at implementation of a simple GAN using Keras

  • ChaiPy

    0.4 8.1 Python
    A developer interface for creating Chat AIs for the Chai app.
Run Linux Software Faster and Safer than Linux with Unikernels
sponsored github.com/nanovms

Popular Comparisons

SaaSHub - Software Alternatives and Reviews
sponsored www.saashub.com

Add another 'Machine Learning' Package