datatap-python
Focus on Algorithm Design, Not on Data Wrangling (by zensors)
seq2seq
A general-purpose encoder-decoder framework for Tensorflow (by google)
Our great sponsors
| datatap-python | seq2seq | |
|---|---|---|
| 9 | 1 | |
| 34 | 5,540 | |
| - | - | |
| 0.0 | 0.0 | |
| over 1 year ago | over 3 years ago | |
| Python | Python | |
| GNU General Public License v3.0 only | Apache License 2.0 |
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.
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.
datatap-python
Posts with mentions or reviews of datatap-python.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-04-06.
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[Project] DataTap provides droplets ( containers for datasets) to make working on popular deep learning datasets easy.
Learn more about how you can start using this here https://github.com/zensors/datatap-python
- Stream any deep learning dataset with just 3 lines of code into Pytorch, Tensorflow or any python project.
- Data droplets make dataset management & sharing simple -- The dataTap Python library is the primary interface for using dataTap's rich data management tools. Create datasets, stream annotations, and analyze model performance all with one library.
- Data droplets specification lets you unify and easily share deep learning datasets. Doplets are designed for complex annotations and let you focus on Deep learning rather than data manipulation.
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The fastest format to store, access & manage labelled data for any deep learning project
http://datatap.dev/ is an open source platform that allows you to easily pull in any data set in a standard format so you can start training a deep learning model in < 3 minutes
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Setting up a feedback loop for performance evaluation and retraining of a model.
You should import the data into https://github.com/zensors/datatap-python, will make managing data for the feedback loop easier
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Show HN: Free user-friendly platform for visual data management
Looking for a user-friendly data management tool? With DataTap, you focus on algorithm design, not on data wrangling. DataTap is a visual data management platform from Zensors.
Check out the repository (https://github.com/zensors/datatap-python)
The dataTap Python library is the primary interface for using dataTap's rich data management tools. Create datasets, stream annotations, and analyze model performance all with one library.
Cool Features
seq2seq
Posts with mentions or reviews of seq2seq.
We have used some of these posts to build our list of alternatives
and similar projects.
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Tegin huvitava avastuse. Google translate tõlkides automaatselt määrab meie ilma soota asesõnad inglise keeles sooliseks olenevalt sellest, mis ametinimetust lauses kasutad.
Treenimiseks antakse masinale (https://github.com/google/seq2seq) väga palju tõlkepaare sisse, kui need tõlkepaarid ongi tänapäevasest stereotüüpsest maailmast siis väga midagi sinna parata ei saa. Keegi teadlikult vähemalt seda masinat stereotüüpseks ei teinud.
What are some alternatives?
When comparing datatap-python and seq2seq you can also consider the following projects:
simpleT5 - simpleT5 is built on top of PyTorch-lightning⚡️ and Transformers🤗 that lets you quickly train your T5 models.
horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.