Data Science Essentials: A Practical Guide
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__Data Science Essentials: A Practical Guide__ is a comprehensive resource designed for beginners and professionals seeking to build a strong foundation in data science. Covering key concepts such as data preprocessing, exploratory data analysis, machine learning, and model evaluation, the book provides step-by-step explanations with real-world examples. It emphasizes practical applications using Python and popular libraries like Pandas, NumPy, and Scikit-Learn. With a focus on hands-on learning, this guide helps readers develop the skills needed to analyze data effectively and make data-drive...
__Data Science Essentials: A Practical Guide__ is a comprehensive resource designed for beginners and professionals seeking to build a strong foundation in data science. Covering key concepts such as data preprocessing, exploratory data analysis, machine learning, and model evaluation, the book provides step-by-step explanations with real-world examples. It emphasizes practical applications using Python and popular libraries like Pandas, NumPy, and Scikit-Learn. With a focus on hands-on learning, this guide helps readers develop the skills needed to analyze data effectively and make data-driven decisions. Whether you're a student, researcher, or industry professional, this book serves as a valuable reference for mastering data science fundamentals.
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