Sacred alternatives and similar packages

Based on the "Machine Learning" category.
Alternatively, view Sacred alternatives based on common mentions on social networks and blogs.

• tensorflow

  10.0 10.0 L1 Sacred VS tensorflow

  An Open Source Machine Learning Framework for Everyone
  

• Keras

  9.9 9.8 L2 Sacred VS Keras

  Deep Learning for humans
  

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• scikit-learn

  9.9 9.9 L3 Sacred VS scikit-learn

  scikit-learn: machine learning in Python
  

• xgboost

  9.8 9.6 L1 Sacred VS 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
  

• gym

  9.8 9.3 Sacred VS gym

  A toolkit for developing and comparing reinforcement learning algorithms.
  

• CNTK

  9.7 0.0 L1 Sacred VS CNTK

  Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
  

• PaddlePaddle

  9.6 10.0 L1 Sacred VS PaddlePaddle

  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）
  

• Prophet

  9.5 7.6 Sacred VS Prophet

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

• gensim

  9.5 8.7 L3 Sacred VS gensim

  Topic Modelling for Humans
  

• TFLearn

  9.3 1.2 L3 Sacred VS TFLearn

  Deep learning library featuring a higher-level API for TensorFlow.
  

• MLflow

  9.3 9.6 Sacred VS MLflow

  Open source platform for the machine learning lifecycle
  

• NuPIC

  9.0 0.0 L3 Sacred VS NuPIC

  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 Sacred VS H2O

  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 Sacred VS Surprise

  A Python scikit for building and analyzing recommender systems

• srez

  8.4 0.0 L5 Sacred VS srez

  Image super-resolution through deep learning

• MindsDB

  8.0 9.9 Sacred VS MindsDB

  Predictive AI layer for existing databases.
  

• Pylearn2

  8.0 1.2 L2 Sacred VS Pylearn2

  Warning: This project does not have any current developer. See bellow.
  

• LightFM

  7.9 4.3 L4 Sacred VS LightFM

  A Python implementation of LightFM, a hybrid recommendation algorithm.
  

• PyBrain

  7.8 0.0 L4 Sacred VS PyBrain

  Another Python Machine Learning Library.

• skflow

  7.6 1.3 L4 Sacred VS skflow

  Simplified interface for TensorFlow (mimicking Scikit Learn) for Deep Learning
  

• Clairvoyant

  7.4 1.1 L3 Sacred VS Clairvoyant

  Software designed to identify and monitor social/historical cues for short term stock movement

• python-recsys

  6.4 0.0 L4 Sacred VS python-recsys

  A python library for implementing a recommender system

• Metrics

  6.3 0.0 Sacred VS Metrics

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

• pydeep

  6.2 0.0 L3 Sacred VS pydeep

  Deep learning in Python

• awesome-embedding-models

  6.0 0.0 Sacred VS awesome-embedding-models

  A curated list of awesome embedding models tutorials, projects and communities.

• Crab

  5.9 0.0 L2 Sacred VS Crab

  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 7.8 Sacred VS karateclub

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

• hebel

  5.2 0.0 L2 Sacred VS hebel

  GPU-Accelerated Deep Learning Library in Python

• seqeval

  4.0 0.4 Sacred VS seqeval

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

• SciKit-Learn Laboratory

  3.9 8.1 Sacred VS SciKit-Learn Laboratory

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

• adaptive

  3.9 9.1 Sacred VS adaptive

  :chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions
  

• rwa

  3.9 0.0 L5 Sacred VS rwa

  Machine Learning on Sequential Data Using a Recurrent Weighted Average

• pdpipe

  3.7 5.0 Sacred VS pdpipe

  Easy pipelines for pandas DataFrames.
  

• Feature Forge

  3.5 0.0 L4 Sacred VS Feature Forge

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

• brew

  3.2 0.0 L4 Sacred VS brew

  Multiple Classifier Systems and Ensemble Learning Library in Python.

• Data Flow Facilitator for Machine Learning (dffml)

  2.9 9.7 Sacred VS Data Flow Facilitator for Machine Learning (dffml)

  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 Sacred VS MLP Classifier

  A handwritten multilayer perceptron classifer using numpy.

• bodywork

  2.7 9.4 Sacred VS bodywork

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

• nptyping

  2.6 6.3 Sacred VS nptyping

  💡 Type hints for Numpy

• vowpal_porpoise

  2.4 0.0 L3 Sacred VS vowpal_porpoise

  lightweight python wrapper for vowpal wabbit

• tfgraphviz

  1.3 2.7 L5 Sacred VS tfgraphviz

  A visualization tool to show a TensorFlow's graph like TensorBoard

• neptune-contrib

  1.3 5.6 Sacred VS neptune-contrib

  This library is a location of the LegacyLogger for PyTorch Lightning.
  

• Simple GAN

  0.6 0.0 Sacred VS Simple GAN

  Attempt at implementation of a simple GAN using Keras

• ChaiPy

  0.3 7.9 Sacred VS ChaiPy

  A developer interface for creating Chat AIs for the Chai app.
  

* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.

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Popular Comparisons

• Sacred
  vs
  MLflow
• Sacred
  vs
  Clairvoyant
• Sacred
  vs
  tensorflow
• Sacred
  vs
  Keras
• Sacred
  vs
  scikit-learn

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