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    Google Gemini for Python: Coding with Bard

    Google Gemini for Python by Campesato, Oswald;

    Coding with Bard

    Series: MLI Generative AI Series;

      • GET 20% OFF

      • The discount is only available for 'Alert of Favourite Topics' newsletter recipients.
      • Publisher's listprice EUR 49.95
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        19 510 Ft (18 581 Ft + 5% VAT)
      • Discount 20% (cc. 3 902 Ft off)
      • Discounted price 15 608 Ft (14 865 Ft + 5% VAT)
      • Discount is valid until: 30 June 2026

    19 510 Ft

    db

    Availability

    printed on demand

    Why don't you give exact delivery time?

    Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.

    Long description:

    This book provides a bridge between the worlds of Python 3 programming and Generative AI, aiming to equip readers with the skills to navigate both domains with confidence. It begins with an introduction to fundamental aspects of Python programming, which include various data types, number formatting, Unicode and UTF-8 handling, and text manipulation techniques. In addition, you will learn about loops, functions, data structures, NumPy, Pandas, conditional logic, and reserved words in Python. Further chapters show how to handle user input, manage exceptions, and work with command-line arguments. The text then transitions to the realm of Generative AI, discussing its distinction from Conversational AI. Popular platforms and models, including Bard (now called “Gemini”) and its competitors, are presented to give readers an understanding of the current AI landscape. The book discusses the capabilities of Bard, its strengths, weaknesses, and potential applications. Finally, you will learn how to generate a variety of Python 3 code samples via Bard.

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