The data science workflow generally involves four main steps: data wrangling, exploratory data analysis, modeling, and evaluation. Data wrangling is the process of cleaning and preparing data for analysis. Exploratory data analysis is the process of exploring data to find patterns and relationships. Modeling is the process of building models to make predictions or recommendations based on data. Evaluation is the process of assessing the accuracy of models and using them to make decisions.
