Running ML code inside Docker Container

Step 1:

Building code one the Jupyter Notebook or any other IDE on windows .

Saving model for future use

Step 2:

Transfering ML code and the database file from windows to the Linux Vm using WinScp tool .

Step 3:

From Linux VM launching a docker container from Centos image .

To run the code in docker container we require the code as well as the database inside it . so we use the docker cp command to copy the data inside the running container . also we use the Volume mount aslo here instead of “cp” .

Step 4:

Once the complete environment is set for the code , the run the code inside docker container .

Also the model is saved here in the directory , whic is loaded and used here for prediction.