How to Create Your machine learning and inside a docker container
The plan is like this ..
👉 Pull the Docker container image of CentOS image from DockerHub and create a new container
👉 Install the Python software on the top of docker container
👉 In Container you need to copy/create machine learning model which you have created in jupyter notebook
Step 1:Decide what machine learning program you want to copy inside docker container and the dataset it require to get trained
Step 2: making the dockerfile
RUN yum install python38 -y
RUN pip3 install scikit-learn
RUN pip3 install pandas
RUN pip3 install matplotlib
COPY ml.py /home/
COPY SalaryData.csv /home/
first we take the base container image for the dockerfile which here is centos
them we install python3 in that container image.
then we install scikit-learn , pandas, matplotlib module using pip command , inside the cotainer, in the lines ,
RUN pip3 install matplolib,scikit-learn,pandas,
then finally we COPY the program file from the computer to the container image ,and dataset also , using the COPY command , whose first parameter is from source , and then to destination.
Then we execute CMD command
to run the machine learning code inside the container whenever the container is deployed.
we build the code using docker build command , and assuming that all the required files are in the same folder and the pwd is inside the folder .
docker build -t whatever_your_tag:whatever_your _version .
the dot in the end tells where the Dockerfile file is located which in this case is the current directory.
Here is a screenshot for the working example of the code.