follows a structured and comprehensive three-tiered approach packed with hands-on examples and code. Part 2 details standard machine learning pipelines, with an emphasis on data processing analysis, feature engineering, and modeling. You will learn how to process, wrangle, summarize and visualize data in its various forms. Feature engineering and selection methodologies will be covered in detail with real-world datasets followed by model building, tuning, interpretation and deployment. IT professionals, analysts, developers, data scientists, engineers, graduate students weiterlesen