LightFM VS scikit-learn

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

LightFM

A Python implementation of LightFM, a hybrid recommendation algorithm. (by lyst)

scikit-learn

scikit-learn: machine learning in Python (by scikit-learn)
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LightFM scikit-learn
0 39
4,068 50,599
0.8% 0.8%
6.2 9.9
4 months ago 5 days ago
Python Python
MIT License BSD 3-clause "New" or "Revised" 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.

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.

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 2022-06-23.

What are some alternatives?

When comparing LightFM and scikit-learn you can also consider the following projects:

Surprise - A Python scikit for building and analyzing recommender systems

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.

tensorflow - An Open Source Machine Learning Framework for Everyone

gensim - Topic Modelling for Humans

PyBrain

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.

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

implicit - Fast Python Collaborative Filtering for Implicit Feedback Datasets

MLflow - Open source platform for the machine learning lifecycle