datatap-python
iterative-stratification
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| datatap-python | iterative-stratification | |
|---|---|---|
| 9 | 1 | |
| 34 | 817 | |
| - | - | |
| 0.0 | 0.0 | |
| over 1 year ago | almost 2 years ago | |
| Python | Python | |
| GNU General Public License v3.0 only | BSD 3-clause "New" or "Revised" License |
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datatap-python
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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
iterative-stratification
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TypeError: unhashable type: 'list' when preparing index of labels for MultiLabelBinarizer
I need to create this so I can encode the Labels and run iterative stratification as detailed [here](https://github.com/trent-b/iterative-stratification). Once I have the index prepared, i will run MultiLabelBinarizer to encode the "Labels" list and create a matrix of those values. I will then run the stratification sampling algorithm on that matrix to determine zero-based train and test indices. The code I have below is causing an error.
What are some alternatives?
simpleT5 - simpleT5 is built on top of PyTorch-lightning⚡️ and Transformers🤗 that lets you quickly train your T5 models.
auto-sklearn - Automated Machine Learning with scikit-learn
whylogs - An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collection, ensuring safety & robustness. 📈
best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
seq2seq - A general-purpose encoder-decoder framework for Tensorflow
Dask - Parallel computing with task scheduling
coral-cnn - Rank Consistent Ordinal Regression for Neural Networks with Application to Age Estimation
timebasedcv - Time based splits for cross validation
Schematics - Python Data Structures for Humans™.
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