pyRDF2Vec VS gensim

Compare pyRDF2Vec vs gensim and see what are their differences.

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pyRDF2Vec gensim
1 11
150 13,187
4.0% 1.2%
6.6 7.8
13 days ago 14 days ago
Python Python
MIT License GNU Lesser General Public License v2.1 only
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.


Posts with mentions or reviews of pyRDF2Vec. We have used some of these posts to build our list of alternatives and similar projects.
  • [P] pyRDF2Vec 0.2.0 is out!
    1 project | | 22 Mar 2021
    This release is packed with many new features and optimizations under the hood. An entire overview of what's new can be found in our CHANGELOG ( An overview of some major updates:


Posts with mentions or reviews of gensim. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-01-17.

What are some alternatives?

When comparing pyRDF2Vec and gensim you can also consider the following projects:

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

BERTopic - Leveraging BERT and c-TF-IDF to create easily interpretable topics.

tensorflow - An Open Source Machine Learning Framework for Everyone

MLflow - Open source platform for the machine learning lifecycle

Keras - Deep Learning for humans

flair - A very simple framework for state-of-the-art Natural Language Processing (NLP)

fuzzywuzzy - Fuzzy String Matching in Python

GuidedLDA - semi supervised guided topic model with custom guidedLDA

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

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

MLP Classifier - A handwritten multilayer perceptron classifer using numpy.

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