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.

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