curiousily / Deploy-Keras-Deep-Learning-Model-with-Flask

Build Deep Neural Network model in Keras and deploy a REST API to production with Flask on Google App Engine

Zero to Production

It is not recommended to deploy your production models as shown here. This is just an end-to-end example to get started quickly.

Read the complete guide

This guide shows you how to:

• build a Deep Neural Network that predicts Airbnb prices in NYC (using scikit-learn and Keras)
• build a REST API that predicts prices based on the model (using Flask and gunicorn)
• deploy the model to production on Google App Engine

Quick start

Requirements:

• Python 3.7
• Google Cloud Engine account
• Google Cloud SDK

Clone this repository:

git clone [e-mail]:curiousily/End-to-End-Machine-Learning-with-Keras.git
cd End-to-End-Machine-Learning-with-Keras

Install libraries:

pip install -r requirements.txt

Start local server

flask run

Make predictions

curl -d '{"neighbourhood_group": "Brooklyn", "latitude": 40.64749, "longitude": -73.97237, "room_type": "Private room", "minimum_nights": 1, "number_of_reviews": 9, "calculated_host_listings_count": 6, "availability_365": 365}' -H "Content-Type: application/json" -X POST http://localhost:5000

Deploy to Google App Engine

gcloud app deploy

Read the complete guide