H2O VS LightFM

Compare H2O vs LightFM 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)

LightFM

A Python implementation of LightFM, a hybrid recommendation algorithm. (by lyst)
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H2O LightFM
10 0
6,684 4,579
0.9% 1.0%
9.7 4.8
about 19 hours ago 3 months ago
Jupyter Notebook Python
Apache License 2.0 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.

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 2023-07-12.

LightFM

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

We haven't tracked posts mentioning LightFM yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing H2O and LightFM you can also consider the following projects:

Surprise - A Python scikit for building and analyzing recommender systems

tensorflow - An Open Source Machine Learning Framework for Everyone

MLflow - Open source platform for the machine learning lifecycle

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

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

implicit - Fast Python Collaborative Filtering for Implicit Feedback Datasets

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.

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

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

spotlight - Deep recommender models using PyTorch.

FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.