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GitHub / SidNimbalkar / Sentiment-Analysis-Pipeline-in-Metaflow-serviced-by-Flask-API
We create labelled dataset using Edgar earning calls, train a TensorFlow model using said dataset and then create a REST API using flask to perform sentiment analysis.
Stars: 0
Forks: 1
Open Issues: 3
License: None
Language: Python
Repo Size: 1.57 MB
Dependencies:
45
Created: about 4 years ago
Updated: about 4 years ago
Last pushed: over 1 year ago
Last synced: about 1 year ago
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Dependencies
- black *
- boto3 *
- coloredlogs *
- flake8 *
- flask *
- gunicorn *
- metaflow *
- numpy *
- pandas *
- pyyaml *
- scikit-learn *
- tensorflow-datasets *
- tensorflow-hub *
requirements.txt
pypi
- Flask ==1.1.1
- Keras ==2.3.1
- Keras-Applications ==1.0.8
- Keras-Preprocessing ==1.1.0
- auth ==0.5.3
- beautifulsoup4 ==4.8.0
- boto3 ==1.12.3
- google-cloud-language ==1.3.0
- google-cloud-natural-language ==0.24.0
- json5 ==0.8.5
- metaflow ==2.0.2
- numpy ==1.17.2
- oauth2client ==3.0.0
- oauthlib ==3.1.0
- pandas ==1.0.1
- s3fs ==0.4.0
- s3transfer ==0.3.3
- scikit-image ==0.15.0
- scikit-learn ==0.22.1
- scipy ==1.4.1
- seaborn ==0.9.0
- selenium ==3.141.0
- six ==1.12.0
- sklearn ==0.0
- smart-open ==1.9.0
- smartopen ==0.2
- tensorflow ==2.1.0
- tensorflow-estimator ==2.1.0
- tensorflow-hub ==0.7.0
- tensorflow-metadata ==0.21.1
- textblob ==0.15.3
- urllib3 ==1.24.2