MatchZoo | Facilitating the design , comparison and sharing | Natural Language Processing library

by NTMC-Community Python Version: 2.2.0 License: Apache-2.0

X-Ray Key Features Code Snippets(4)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | MatchZoo Summary

MatchZoo is a Python library typically used in Artificial Intelligence, Natural Language Processing, Deep Learning, Pytorch applications. MatchZoo has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can install using 'pip install MatchZoo' or download it from GitHub, PyPI.

Facilitating the design, comparison and sharing of deep text matching models. MatchZoo 是一个通用的文本匹配工具包，它旨在方便大家快速的实现、比较、以及分享最新的深度文本匹配模型。. News: MatchZoo-py (PyTorch version of MatchZoo) is ready now. The goal of MatchZoo is to provide a high-quality codebase for deep text matching research, such as document retrieval, question answering, conversational response ranking, and paraphrase identification. With the unified data processing pipeline, simplified model configuration and automatic hyper-parameters tunning features equipped, MatchZoo is flexible and easy to use.

Support

Quality

Security

License

Reuse

Support

MatchZoo has a medium active ecosystem.

It has 3773 star(s) with 916 fork(s). There are 176 watchers for this library.

It had no major release in the last 12 months.

There are 33 open issues and 430 have been closed. On average issues are closed in 208 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of MatchZoo is 2.2.0

Quality

MatchZoo has 0 bugs and 0 code smells.

Security

MatchZoo has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

MatchZoo code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

MatchZoo is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

MatchZoo releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed MatchZoo and discovered the below as its top functions. This is intended to give you an instant insight into MatchZoo implemented functionality, and help decide if they suit your requirements.

Build the model
Create an embedding layer
Create an output layer
Creates a keraset
Connects the model
Create a keras layer
Calculate the average of texts
Return default parameters for the model
Adds a Param instance
Return the default params
Runs the optimizer
Connects the convolution layer
Return default parameters
Apply transform to data_pack
Apply transformation to data_pack
Get default params
Prepare a trained model
Build the embedding layer
Calculate recurrent unit
Load data from matchzoo
Train the model
Call the forward match function
Build the graph
Pack data into MatchZoo
Parse metric from metric name
Builds the embedding layer
Apply transform to the data_pack

Get all kandi verified functions for this library.

MatchZoo Key Features

No Key Features are available at this moment for MatchZoo.

MatchZoo Examples and Code Snippets

default

Python

Lines of Code : 140

License : No License

Copy

 >>> f = DFAFilter()
 >>> f.add("sexy")
 >>> f.filter("hello sexy baby")
 hello **** baby

>>> import langid
>>> langid.classify("This is a test")
('en', -54.41310358047485)

from langdetect import detect

NeuralResponseRanking,Guide To Use,DMN

Python

Lines of Code : 87

License : Permissive (MIT)

Copy

label  \t   utterance_1   \t   utterance_2    \t     ......    \t    candidate_response

.
├── ms_v2
│   ├── ModelInput
│   │   ├── dmn_model_input
│   │   └── dmn_prf_model_input_body
│   └

NeuralResponseRanking

Python

Lines of Code : 11

License : Permissive (MIT)

Copy

Liu Yang, Minghui Qiu, Chen Qu, Jiafeng Guo, Yongfeng Zhang, W. Bruce Croft, Jun Huang, Haiqing Chen. Response Ranking
with Deep Matching Networks and External Knowledge in Information-seeking Conversation Systems. In Proceedings of the
41th Internat

I can't get a value with key in python dictionary

Python

Lines of Code : 6

License : Strong Copyleft (CC BY-SA 4.0)

Copy

history.history[list(history.history.keys())[2]]

history.history[list(history.history.keys())[3]]

type(list(history.history.keys())[2])

Community Discussions

Trending Discussions on MatchZoo

I can't get a value with key in python dictionary

QUESTION

I can't get a value with key in python dictionary

Asked 2020-Dec-09 at 11:49

I'm using 'Matchzoo' text retrieval library which is based on keras. I want to use the trained result, but it's dictionary and I can't get the value with shown keys.

After training the model,

...

ANSWER

Answered 2020-Dec-09 at 11:49

As you said, it could be because they are not strings. If you are sure that's the order they are coming in, try indexing through the dictionary using the keys as shown below..

Source https://stackoverflow.com/questions/65214416

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install MatchZoo

To train a Deep Semantic Structured Model, import matchzoo and prepare input data. Preprocess your input data in three lines of code, keep track parameters to be passed into the model.
MatchZoo is dependent on Keras and Tensorflow. Two ways to install MatchZoo:.

Support

Please make sure to read the Contributing Guide before creating a pull request. If you have a MatchZoo-related paper/project/compnent/tool, send a pull request to this awesome list!.

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