twitter_sentiment_analysis | sentiment analysis and topic modelling | Topic Modeling library

by nagarmayank Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | twitter_sentiment_analysis Summary

twitter_sentiment_analysis is a Python library typically used in Artificial Intelligence, Topic Modeling, Bert, Neural Network applications. twitter_sentiment_analysis has no bugs, it has no vulnerabilities and it has low support. However twitter_sentiment_analysis build file is not available. You can download it from GitHub.

This repository helps in doing Sentiment Analysis and Topic Modelling.

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Support

twitter_sentiment_analysis has a low active ecosystem.

It has 4 star(s) with 2 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

twitter_sentiment_analysis has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of twitter_sentiment_analysis is current.

Quality

twitter_sentiment_analysis has no bugs reported.

Security

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

License

twitter_sentiment_analysis does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

twitter_sentiment_analysis releases are not available. You will need to build from source code and install.

twitter_sentiment_analysis has no build file. You will be need to create the build yourself to build the component from source.

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twitter_sentiment_analysis Key Features

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twitter_sentiment_analysis Examples and Code Snippets

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Community Discussions

Trending Discussions on twitter_sentiment_analysis

OSError: SavedModel file does not exist when I try to deploy my Flask application on Heroku

Serving retrained Tensorflow Hub module with new features

QUESTION

OSError: SavedModel file does not exist when I try to deploy my Flask application on Heroku

Asked 2020-Nov-19 at 06:08

My flask application works fine on my local server. When I try to deploy it on heroku it give the following error:

2020-11-12T13:22:11.503563+00:00 app[web.1]: OSError: SavedModel file does not exist at: /Users/leylamemiguven/Desktop/sentiment/twitter_sentiment_analysis.h5/{saved_model.pbtxt|saved_model.pb}

My keras model is saved as a .h5 file in the root directory of the project. The path is correct as I directly copied the path from vs code. I can't seem to figure out the issue because it works just fine when I run it with $ flask run Here is the model. py file

...

ANSWER

Answered 2020-Nov-19 at 06:08

Your file path looks like it's relative to your local PC

Source https://stackoverflow.com/questions/64805010

QUESTION

Serving retrained Tensorflow Hub module with new features

Asked 2018-Nov-09 at 10:28

I have trained a Tensorflow model using estimators and TF Hub Elmo word embedding + new features, and have been trying to get it working with Tensorflow Serving for predictions. When I try to run a prediction, I get the following error:

...

ANSWER

Answered 2018-Nov-09 at 10:28

The error you're seeing is about a mismatch between the signatures in the SavedModel: the estimator does not write the one you are trying to serve. The saved_model_cli should help you inspect it.

Also, your code uses the long-obsolete tf.contrib.estimator and mixes it with tf.estimator. I highly recommend switching to tf.estimator throughout.

This seems unrelated to the use of TensorFlow Hub. By the time your estimator exports a model, all module contents have been inlined into it.

Source https://stackoverflow.com/questions/53199932

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

Vulnerabilities

No vulnerabilities reported

Install twitter_sentiment_analysis

You can download it from GitHub.
You can use twitter_sentiment_analysis like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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