scikit-learn VS H2O

Compare scikit-learn vs H2O and see what are their differences.

scikit-learn

scikit-learn: machine learning in Python (by scikit-learn)

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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scikit-learn H2O
61 6
52,699 6,123
0.5% 0.5%
9.9 9.8
7 days ago 1 day ago
Python Jupyter Notebook
BSD 3-clause "New" or "Revised" 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.

scikit-learn

Posts with mentions or reviews of scikit-learn. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-01-25.

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 scikit-learn and H2O you can also consider the following projects:

Keras - Deep Learning for humans

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

Surprise - A Python scikit for building and analyzing recommender systems

tensorflow - An Open Source Machine Learning Framework for Everyone

gensim - Topic Modelling for Humans

MLflow - Open source platform for the machine learning lifecycle

PyBrain

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

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.

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