100-days-mlops-kodekloud

Create a Python Virtual Environment for ML

Problem

The xFusionCorp Industries data science team needs a standardised Python environment for their new ML project. Set up a virtual environment with the required ML libraries on the controlplane host.

1. Create a Python virtual environment named ml-env under /root/code/ using python3 -m venv.

2. Activate the environment and install the following packages: numpy, pandas, scikit-learn, and matplotlib.

3. Generate a requirements.txt file using pip freeze and save it at /root/code/requirements.txt.

Solution

1. Create virtual environment in ml-env.

    python3 -m venv ml-env
   

2. Activate enviornment, then install ML packages.

    source ml-env/bin/activate
    pip install numpy pandas scikit-learn matplotlib
   

3. Freeze installed packages into requirements.txt

    pip freeze > requirements.txt
   

4. To test run the following command

    pip install -r requirements.txt
   

   It will ensure that you already installed thoose packages

This site is open source. Improve this page.