Google Gemini for Python: Coding with Bard (MLI Generative AI Series)

Campesato, Oswald

ISBN 10: 1501522744 / ISBN 13: 9781501522741

Verlag: Mercury Learning and Information, 2024

Bestandsnummer des Verkäufers mon0003582093

Inhaltsangabe:

This book provides a bridge between the worlds of Python 3 programming and Generative AI, equipping 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. FEATURES: Includes a chapter on how to generate a variety of Python 3 code samples via Gemini Covers basic concepts of Python 3 such as loops, conditional logic, reserved words, user input, manage exceptions, work with command-line arguments, and more Includes companion files for downloading with source code and figures

Über die Autorin bzw. den Autor: Oswald Campesato specializes in Deep Learning, Python, Data Science, and generative AI. He is the author/co-author of over forty books including Google Gemini for Python, Data Cleaning, and GPT-4 for Developers (all Mercury Learning).

Bibliografische Details

Titel: Google Gemini for Python: Coding with Bard (...
Verlag: Mercury Learning and Information
Erscheinungsdatum: 2024
Einband: paperback
Zustand: Very Good