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Handling Pipelines in Data Science with Jenkins  Using Jenkins for Data Science Pipelines Jenkins is a popular open-source automation server that supports  Continuous Integration and Continuous Deployment (CI/CD) . It is highly customizable and can automate various stages of a data science pipeline, including data extraction, transformation, model training, and deployment. Create a Git repository ✔ Store: Dataset Python scripts ML models Jenkinsfile Common Pipeline Stages: Data Extraction Data Cleaning & Transformation Feature Engineering Model Training Model Evaluation Model Deployment Sample Jenkins Pipeline Flow Code Commit → Jenkins Trigger → Data Processing → Model Training → Evaluation → Deployment → Monitoring In this guide, we will explore the  step-by-step pipeline of data science using Jenkins , understand how each stage works, and see how Jenkins simplifies the end-to-end machine learning workflow. Steps to Set Up a Data Sc...