semvec/pypi-packages huggingface dataset:
sidsd21 0.0.1
A package to detect intent from utterances.
Requires Python: >=3.6

# Intent Recognition

This is a package to detect intent of utterances, trained on the SNIPS dataset.

It can detection any of the following intents in an input utterance:
1. PlayMusic	
2. GetWeather	
3. BookRestaurant	
4. RateBook	
5. SearchScreeningEvent	
6. SearchCreativeWork	
7. AddToPlaylist	

Example usage:

import intent_recognition

predictor = intent_recognition.Predictor()

confidence, pred_intent = predictor("find animated movies playing near me")
HyperclassifierSearch 1.0
Train multiple classifiers/pipelines
Requires Python: >=3.0

# HyperclassifierSearch

## General info
HyperclassifierSearch allows to train multiple classifiers/pipelines in Python with GridSearchCV or RandomizedSearchCV.

## Installation
`pip install HyperclassifierSearch`

## Requirements
The code was developed in Python 3. The execution needs Pandas and scikit-learn, i.e. GridSearchCV and RandomizedSearchCV.

## Enhancements and credits
The package is build based on code from [David Batista](https://github.com/davidsbatista/machine-learning-notebooks/blob/master/hyperparameter-across-models.ipynb).

1. documentation enhancements:
- examples how to search the best model over multiple Pipelines using different classifiers
- added code documentation including docstrings

2. functionality enhancements:
- added option to use RandomizedSearchCV
- the best overall model is provided by train_model()
- output dataframe is simplified as standard option

## Examples
See [HyperclassifierSearch on GitHub](https://github.com/dabln/HyperclassifierSearch).
sidsd20 0.0.1
A package to detect intent from utterances.
Requires Python: >=3.6

# Intent Recognition

This is a package to detect intent of utterances, trained on the SNIPS dataset.

It can detection any of the following intents in an input utterance:
1. PlayMusic	
2. GetWeather	
3. BookRestaurant	
4. RateBook	
5. SearchScreeningEvent	
6. SearchCreativeWork	
7. AddToPlaylist	

Example usage:

import intent_recognition

predictor = intent_recognition.Predictor()

confidence, pred_intent = predictor("find animated movies playing near me")
sidsd19 0.0.1
A package to detect intent from utterances.
Requires Python: >=3.6

# Intent Recognition

This is a package to detect intent of utterances, trained on the SNIPS dataset.

It can detection any of the following intents in an input utterance:
1. PlayMusic	
2. GetWeather	
3. BookRestaurant	
4. RateBook	
5. SearchScreeningEvent	
6. SearchCreativeWork	
7. AddToPlaylist	

Example usage:

import intent_recognition

predictor = intent_recognition.Predictor()

confidence, pred_intent = predictor("find animated movies playing near me")
sidsd18 0.0.1
A package to detect intent from utterances.
Requires Python: >=3.6

# Intent Recognition

This is a package to detect intent of utterances, trained on the SNIPS dataset.

It can detection any of the following intents in an input utterance:
1. PlayMusic	
2. GetWeather	
3. BookRestaurant	
4. RateBook	
5. SearchScreeningEvent	
6. SearchCreativeWork	
7. AddToPlaylist	

Example usage:

import intent_recognition

predictor = intent_recognition.Predictor()

confidence, pred_intent = predictor("find animated movies playing near me")