neptune-contrib VS H2O

Compare neptune-contrib vs H2O and see what are their differences.

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. (by h2oai)
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neptune-contrib H2O
0 4
26 5,985
- 1.3%
1.0 9.8
12 months ago 5 days ago
Python Jupyter Notebook
MIT License Apache License 2.0
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.

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.

H2O

Posts with mentions or reviews of H2O. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-06-14.

What are some alternatives?

When comparing neptune-contrib and H2O you can also consider the following projects:

MLflow - Open source platform for the machine learning lifecycle

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

LightGBM - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

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

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

MindsDB - In-Database Machine Learning

pycaret - An open-source, low-code machine learning library in Python

FLAML - A fast library for AutoML and tuning.

tensorflow - An Open Source Machine Learning Framework for Everyone

LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.

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)