TabularSemanticParsing VS fake-news

Compare TabularSemanticParsing vs fake-news and see what are their differences.

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TabularSemanticParsing fake-news
1 1
214 130
0.5% -
0.0 4.1
11 months ago over 3 years ago
Jupyter Notebook Jupyter Notebook
BSD 3-clause "New" or "Revised" License GNU Affero General Public License v3.0
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.

TabularSemanticParsing

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

fake-news

Posts with mentions or reviews of fake-news. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-02-06.

What are some alternatives?

When comparing TabularSemanticParsing and fake-news you can also consider the following projects:

ecco - Explain, analyze, and visualize NLP language models. Ecco creates interactive visualizations directly in Jupyter notebooks explaining the behavior of Transformer-based language models (like GPT2, BERT, RoBERTA, T5, and T0).

onepanel - The open source, end-to-end computer vision platform. Label, build, train, tune, deploy and automate in a unified platform that runs on any cloud and on-premises.

ml-course - Open Machine Learning course

mt5-M2M-comparison - Comparing M2M and mT5 on a rare language pairs, blog post: https://medium.com/@abdessalemboukil/comparing-facebooks-m2m-to-mt5-in-low-resources-translation-english-yoruba-ef56624d2b75

pytorch-sentiment-analysis - Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

fastMONAI - Simplifying deep learning for medical imaging

Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.

mlf-core - CPU and GPU deterministic and therefore fully reproducible machine learning pipelines using MLflow.