Tune the parameters of a VotingClassifer or VotingRegressor
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Course Description
scikit-learn,
in this course we will learn about scikit-learn, one of the most powerful and widely used machine learning libraries in Python. You will explore how to build and evaluate machine learning models using tools for classification, regression, clustering, dimensionality reduction, and model selection. The course will guide you through essential steps like data preprocessing, splitting datasets, choosing the right algorithms, and fine-tuning model performance with cross-validation and grid search. You will also work with pipelines to streamline workflows and manage complex ML tasks more efficiently. With hands-on examples and real-world datasets, you will gain practical skills to implement models that make accurate predictions. Whether you're a beginner or looking to solidify your ML foundation, this course will help you master machine learning with scikit-learn and apply it confidently in data science projects. Basic Python and data handling knowledge are recommended. Data School
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