4. Productization

Activity 4.01: Deploying a Deep Learning Application

Solution:

In this activity, we deploy our model as a web application locally. This allows us to connect to the web application using a browser or to use another application through the application's HTTP API. You can find the code for this activity at https://packt.live/2Zdor2S.

1. Using your Terminal, navigate to the cryptonic directory and build the Docker images for all the required components:

   $ docker build --tag cryptonic:latest .
   $ docker build --tag cryptonic-cache:latest       cryptonic-cache/

   Those two commands build the two images that we will use in this application: cryptonic (containing the Flask application) and cryptonic-cache (containing the Redis cache).

2. After building the images, identify the docker-compose.yml file and open it in a text editor. Change the BITCOIN_START_DATE parameter to a date other than 2017-01-01:

   BITCOIN_START_DATE = # Use other date here

3. As a final step...