Data Science Lifecycle.

    Data Science Lifecycle: Stages, Importance, Examples
    Problem Definition.
    Data Collection.
    Data Cleaning and Preprocessing.
    Exploratory Data Analysis (EDA)
    Model Building.
    Model Evaluation.
    Deployment and Maintenance.