chess VS neptune-contrib

Compare chess vs neptune-contrib and see what are their differences.

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chess neptune-contrib
2 0
13 26
- -
7.0 2.1
7 months ago 10 months ago
Python Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

chess

Posts with mentions or reviews of chess. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-12-02.

neptune-contrib

Posts with mentions or reviews of neptune-contrib. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning neptune-contrib yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing chess and neptune-contrib you can also consider the following projects:

tensorflow - An Open Source Machine Learning Framework for Everyone

Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros

Keras - Deep Learning for humans

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

lightning-hydra-template - PyTorch Lightning + Hydra. A very user-friendly template for rapid and reproducible ML experimentation with best practices. ⚡🔥⚡

gym - A toolkit for developing and comparing reinforcement learning algorithms.

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

MLflow - Open source platform for the machine learning lifecycle

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

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.

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

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