https://github.com/machinelearningzuu/model-deployment-with-flask-and-tensorflow.js

with the development of model effiency, processing capabilities and accuarcy we need good tools to effient our deployment aswell.
https://github.com/machinelearningzuu/model-deployment-with-flask-and-tensorflow.js

Last synced: about 1 year ago
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with the development of model effiency, processing capabilities and accuarcy we need good tools to effient our deployment aswell.

• Host: GitHub
• URL: https://github.com/machinelearningzuu/model-deployment-with-flask-and-tensorflow.js
• Owner: machinelearningzuu
• Created: 2020-03-03T15:40:36.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2020-04-08T02:56:43.000Z (about 6 years ago)
• Last Synced: 2025-02-04T17:17:32.420Z (over 1 year ago)
• Language: Python
• Homepage:
• Size: 6.84 KB
• Stars: 1
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
#Model-Deployment-with-Flask-and-Tensorflow.js

Its not only enough to explore through modeling and training without any touch of model deployment. Model deployment is the 

most necessary task while desiging models for industrial purposes. We have several deployment methods like using RestAPIs,

Heroku App , cloud based architrctures, but tensorflow introduced such powerful tool named tensorflow.js that you can deploy 

your models in the web browser. you need good understanding of Java script to handle tensorflow.js . the embedded models like 

mobile net computer vision architecture can deploy really easily with the help of such a tools.