✴️Creating ML Model inside Docker Container …!! 🐋
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💫 What is Machine Learning ?
👉 Machine learning (ML) is the concept in which machine can learn new things like human beings…,by giving power of intelligence to it. And that power is given by a programmer to the machine.
💫 What is Docker..?
👉 Docker is a tool designed to make it easier to create, deploy, and run applications by using containers. Containers are isolated from one another and bundle their own software, libraries and configuration files, they can communicate with each other through well-defined channels.
Task Description … 📃
➡️ Pull the Docker container image of CentOS image from Docker Hub and create a new container
➡️ Install the Python software on the top of docker container
➡️ In Container you need to deploy machine learning model
Let’s Start ….😃🙌
Step 1: Install Docker
I] Configure yum for Docker :
Create a file “/etc/yum.repos.d/docker.repo”[docker]name=docker repo
baseurl=https://download.docker.com/linux/centos/7/x86_64/stable/gpgcheck=0
When it’s done.., verify by “yum repolist". You see some more software.
II] Install Docker and start service :
# Install Docker
yum install docker-ce -- noblest -y
Then…
# To start docker service
systemctl start docker
# To enable docker service
systemctl enable docker
Step 2: Pull centos image
docker pull centos:latest
Step 3: Launch a container
docker run -it - -name <name_of_OS> centos: latest
Step 4: Install Python36
yum install python36
# Install required libraries
pip3 install pandas
pip3 install scikit-learn
Step 5: Create a Docker image with commit
docker commit <os_name> <image_name>:<version>
Step 6: Launch a container using that image
docker run -it --name<name><image_name_: version>
To verify use “docker images" command
docker images
Step 7: Copy the dataset which we want to work on
```docker cp<location_in_local> <docker_os_name>:<location_in_docker_container>
To verify is it copied or not check inside the docker container
ls
Step 8: Create Linear Regression Model
Step 9: Let’s check our model
The output of our machine learning model is
Thanks for Reaching here…,