Data loaders and abstractions for text and NLP
Project description
LanguageFlow
Data loaders and abstractions for text and NLP
Requirements
Install dependencies
$ pip install future, tox, joblib
$ pip install numpy scipy pandas scikit-learn==0.19.1
$ pip install python-crfsuite==0.9.5
$ pip install Cython
$ pip install -U fasttext --no-cache-dir --no-deps --force-reinstall
$ pip install xgboost
Installation
$ pip install languageflow
Components
Transformers: NumberRemover, CountVectorizer, TfidfVectorizer
Models: SGDClassifier, XGBoostClassifier, KimCNNClassifier, FastTextClassifier, CRF
Data
Download a dataset using download command
$ languageflow download DATASET
List all dataset
$ languageflow list
Datasets
The datasets module currently contains:
PlaintextCorpus: VNESES, VNTQ_SMALL, VNTQ_BIG
CategorizedCorpus: VNTC
History
1.1.7 (2018-04-12)
Automatic deploy with travis and pypi
Fix dependencies hell
1.1.6 (2017-12-26)
Add data module to handle data downloading and data preprocessing
Add many new models: SGDClassifier, XGBoostClassier, FastTextClassifier, CRF
Add new feature: LanguageBoard
Automatic continuous integration with travis-ci
Build docs with readthedocs.org
1.1.5 (2017-12-11)
Refactor project to integrate with underthesea experiment
0.1.0 (2017-09-18)
First release on PyPI.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for languageflow-1.1.12a0-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | c623eee950c6a42d4d316aaefd247d10d3c1dfd17df5b722fed1eb17788c6a97 |
|
MD5 | ff14fd019d5539561c5ac0d73c2df580 |
|
BLAKE2b-256 | 508daa34c1e3689cb280804d098fe61031958e19298ac9f24a5207b45589a1ca |