English
The goal of this book is to provide a step-by-step, project-oriented approach to learning Python for data science. It covers essential topics such as data types, control structures, data wrangling with Pandas, data visualization with Matplotlib and Seaborn, and machine learning with scikit-learn. By integrating theory with application, this book equips readers with the practical tools and problem-solving techniques needed to work confidently with real datasets. The inclusion of case studies and end-of-module assessments ensures that readers can test and deepen their understanding in a meaningful context
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