Deploying Machine Learning Models using Docker containers

Hello everyone.

Welcome you all to my article based on Task-01 of Deploying Machine Learning Models using Docker containers.

Task Description : -

👉 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.

……………………………………………………………………………………….

Steps:-

  1. 👉 Check wheather docker is running or not.

2. 👉 Pull the centos image from Docker hub

3. 👉 Create a Container with the help of Centos image.

4. 👉 Download Python and Git software

5. 👉 Run git clone to clone the GitHub Repository where our Python code is available.

6. 👉 Install all the libraries required for training our Machine Learning model.

7. 👉 Create your LinearRegression Model .

I have created my LinearRegression model with name Model.py

8. 👉 Run the Model.

After execution, we will see that a pickle file named “salary.pkl” has been created.

In the “salary_predictor.py”, we have loaded the pickle file and provided the User Input, and printed the result in an appropriate fashion.

9. 👉 Run the “salary_predictor.py” , to estimate the salary of the Employee.

Thank You …

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