SciKit-Learn Laboratory VS seqeval

Compare SciKit-Learn Laboratory vs seqeval and see what are their differences.

SciKit-Learn Laboratory

SciKit-Learn Laboratory (SKLL) makes it easy to run machine learning experiments. (by EducationalTestingService)

seqeval

A Python framework for sequence labeling evaluation(named-entity recognition, pos tagging, etc...) (by chakki-works)
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SciKit-Learn Laboratory seqeval
0 1
551 1,042
-0.2% 1.2%
8.7 0.0
about 1 month ago 2 months ago
Python Python
BSD 1-Clause License 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.

SciKit-Learn Laboratory

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

We haven't tracked posts mentioning SciKit-Learn Laboratory yet.
Tracking mentions began in Dec 2020.

seqeval

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

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

What are some alternatives?

When comparing SciKit-Learn Laboratory and seqeval you can also consider the following projects:

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

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

Keras - Deep Learning for humans

Metrics - Machine learning evaluation metrics, implemented in Python, R, Haskell, and MATLAB / Octave

tensorflow - An Open Source Machine Learning Framework for Everyone

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

Pylearn2 - Warning: This project does not have any current developer. See bellow.

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

PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)