semvec/pypi-packages huggingface dataset:
assigning-high-impact-pairs 0.0.1
A simple interface for getting high impact pairs from Tamr and assigning them.
Requires Python: >=3.6

# Assigning High Impact Pairs

This package makes it easy to assign pairs to experts using logic based on fields from the unified dataset.
The aim is that engineers will only have to worry about the logic of assigning pairs, rather than the humdrum work of
getting the data in and out of tamr.

It's workflow is:
- Load the unified dataset (UD) for the mastering project. A csv file of the UD is saved locally, along with a version number. 
If the version number of the UD in Tamr differs to the saved version, the latest version will be downloaded and saved.
- Get the high impact pairs (HIP) out of Tamr.
- Join the HIP to the UD
- {Custom user logic to assign HIP to experts}
- Push the assigned pairs back to tamr.
GaborNet 0.1.0
Gabor layer implementation

# GaborNet

[![Coverage][coverage-image]][coverage-url]
[![Build Status][travis-badge]][travis-url]

This research on deep convolutional neural networks proposes a modified architecture that focuses on improving 
convergence and reducing training complexity. The filters in the first layer of network are constrained to fit the 
Gabor function. The parameters of Gabor functions are learnable and updated by standard backpropagation techniques. 
The proposed architecture was tested on several datasets and outperformed the common convolutional networks


[travis-url]: https://travis-ci.com/iKintosh/GaborNet
[travis-badge]: https://travis-ci.com/iKintosh/GaborNet.svg?branch=master
[coverage-image]: https://codecov.io/gh/iKintosh/GaborNet/branch/master/graphs/badge.svg
[coverage-url]: https://codecov.io/gh/iKintosh/GaborNet
python-heideltime-krypton 0.0.2
Python wrapper for Heideltime library.
Requires Python: >=3.6

# Python-HeidelTime

This is a python wrapper for the multilingual temporal tagger HeidelTime.

For more information about this temporal tagger, please visit : https://github.com/HeidelTime/heideltime

Heideltime needs a Part Of Speech Tagger, by default it uses TreeTagger : http://www.cis.uni-muenchen.de/~schmid/tools/TreeTagger/.
This repo includes TreeTagger scripts for Mac and Linux. Windows users will have to download the appropriate scripts from the TreeTagger home page.

# Demo

1. Clone the current github repo: `git clone https://github.com/amineabdaoui/python-heideltime`
2. Install its requirements: `pip install -r requirements.txt`
3. Create a python file in the same directory with the following code:
```python
import HeidelTime
hw = HeidelTime.HeidelTimeWrapper('english')
hw.parse('Neil Armstrong was born in 1930')
```

# Future Work
- Encapsulate the returned tagged string in a python object
- Find a way to install the appropriate POS tagger files according to the user OS.
- Package all the necessary parts in the same python package and release it on PyPi.

`Pull requests` are welcome to improve this wrapper (which is in an early stage).