Data analysis workflow using Scikit-learn
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The data analysis workflow using Scikit-learn comprises three key steps: data preprocessing, model selection and training, and parameter tuning and model evaluation. Data preprocessing involves cleaning, transforming, and preparing the data for analysis. Model selection and training involves choosing the right machine learning model and training it on the data. Parameter tuning and model evaluation involves tuning the hyperparameters of the model and evaluating its performance on a holdout dataset.
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Data analysis workflow using Scikit-learn
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