concise-concepts VS gensim

Compare concise-concepts vs gensim and see what are their differences.

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concise-concepts gensim
1 18
240 15,256
0.8% 0.9%
2.5 7.5
11 months ago 10 days ago
Python Python
MIT License GNU Lesser General Public License v3.0 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.

concise-concepts

Posts with mentions or reviews of concise-concepts. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-10.

gensim

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 2022-12-23.

What are some alternatives?

When comparing concise-concepts and gensim you can also consider the following projects:

huspacy - HuSpaCy: industrial-strength Hungarian natural language processing

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

argilla - Argilla is a collaboration platform for AI engineers and domain experts that require high-quality outputs, full data ownership, and overall efficiency.

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

magnitude - A fast, efficient universal vector embedding utility package.

MLflow - Open source platform for the machine learning lifecycle

tensorflow - An Open Source Machine Learning Framework for Everyone

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