gensim VS pyffs

Compare gensim vs pyffs and see what are their differences.

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gensim pyffs
6 1
12,694 17
0.9% -
9.0 0.0
7 days ago about 2 years ago
Python Python
GNU Lesser General Public License v2.1 only MIT 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.

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 2021-11-22.

pyffs

Posts with mentions or reviews of pyffs. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-06-06.
  • The Levenshtein Distance in Production
    4 projects | news.ycombinator.com | 6 Jun 2021
    Dramatic post ;) It'd be interesting to see concrete benchmarks, on some public data.

    Btw I didn't find the Schulz & Mihov paper that cryptic. You can check its implementation in Python [0], pretty straightforward IMO.

    But I should note that in the end, we chose a simpler approach: the FastSS index. It bypasses constructing / intersecting Levenshtein automata altogether, and is super fast [1].

    [0] https://github.com/antoinewdg/pyffs

    [1] Boytsov, Leonid. (2011). Indexing methods for approximate dictionary searching: Comparative analysis. http://boytsov.info/pubs/sisap2012.pdf

What are some alternatives?

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

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

tensorflow - An Open Source Machine Learning Framework for Everyone

MLflow - Open source platform for the machine learning lifecycle

Keras - Deep Learning for humans

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

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.

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

CNTK - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit

hebel - GPU-Accelerated Deep Learning Library in Python

MLP Classifier - A handwritten multilayer perceptron classifer using numpy.

pdpipe - Easy pipelines for pandas DataFrames.