Description

Book Synopsis

Since the first edition of âœData Science and Analytics with Pythonâ we have witnessed an unprecedented explosion in the interest and development within the fields of Artificial Intelligence and Machine Learning. This surge has led to the widespread adoption of the book, not just among business practitioners, but also by universities as a key textbook. In response to this growth, this new edition builds upon the success of its predecessor, expanding several sections, updating the code to reflect the latest advancements in Python libraries and modules, and addressing the ever-evolving landscape of generative AI (GenAI).

This updated edition ensures that the examples and exercises remain relevant by incorporating the latest features of popular libraries such as Scikit-learn, pandas, and Numpy. Additionally, new sections delve into cutting-edge topics like generative AI, reflecting the advancements and the expanding role these technologies play. This edition also addresses crucia

Data Science and Analytics with Python

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    Order before 4pm today for delivery by Mon 8 Jun 2026.

    A Paperback by Jesus Rogel-Salazar

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      View other formats and editions of Data Science and Analytics with Python by Jesus Rogel-Salazar

      Publisher: CRC Press
      Publication Date: 2/5/2025
      ISBN13: 9781032772493, 978-1032772493
      ISBN10: 1032772492

      Description

      Book Synopsis

      Since the first edition of âœData Science and Analytics with Pythonâ we have witnessed an unprecedented explosion in the interest and development within the fields of Artificial Intelligence and Machine Learning. This surge has led to the widespread adoption of the book, not just among business practitioners, but also by universities as a key textbook. In response to this growth, this new edition builds upon the success of its predecessor, expanding several sections, updating the code to reflect the latest advancements in Python libraries and modules, and addressing the ever-evolving landscape of generative AI (GenAI).

      This updated edition ensures that the examples and exercises remain relevant by incorporating the latest features of popular libraries such as Scikit-learn, pandas, and Numpy. Additionally, new sections delve into cutting-edge topics like generative AI, reflecting the advancements and the expanding role these technologies play. This edition also addresses crucia

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