AI Python Development eBook Bundle by Mercury Learning for $19

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Python: An Introduction to Programming KEY FEATURES This book is an introduction to programming concepts that uses Python 3 as the target language. It follows a practical just-in-time presentation – the material is given to the student when it is needed. Many examples will be based on games because Python has become the language of choice for basic game development. Designed as a Year One textbook for an introduction to programming classes or for the hobbyist who wants to learn the fundamentals of programming, the text assumes no programming experience. Lifetime access on eBooks w/ 600 pages Discover programming concepts that use Python 3 Know some examples based on video game development Know the 4-color throughout with game demos on the companion files Overview on computers programming languages Learn how to write a good program Know how to communicate with the outside world PRODUCT SPECS System Requirements Windows 7 and above macOS Important Details Length of access: lifetime Redemption deadline: redeem your code within 30 days of purchase
Access options: desktop mobile Updates included Mercury Learning and Information provides print and digital content in the areas of science and medicine, technology and computing, engineering, and mathematics (STEM disciplines) designed for the professional/reference, trade, library, higher education, career school, and online training markets. James R. Parker, PhD is a professor of Art and Digital Media at the University of Calgary. His areas of research include computer games and media art, computer simulation, and educational technology. Dr. Parker is the author of several texts, including:Python: Introduction to Programming and Python 3 Pocket Primer. Python for TensorFlow Pocket Primer KEY FEATURES As part of the best-selling Pocket Primer series, this book is designed to prepare programmers for machine learning and deep learning/TensorFlow topics. It begins with a quick introduction to Python, followed by chapters that discuss NumPy, Pandas, Matplotlib, and sci-kit-learn. The final two chapters contain an assortment of TensorFlow 1.x code samples, including detailed code samples for TensorFlow Dataset (which is used heavily in TensorFlow 2 as well). Lifetime access on eBooks w/ 218 pages Practical introduction to Python, NumPy, Pandas Matplotlib Learn about the fundamental aspects of TensorFlow 1.x Understand relevant NumPy/Pandas code samples that are typical in machine learning topics Get to know better some of the useful TensorFlow 1.x code samples for deep learning Get examples of TensorFlow Dataset APIs with lazy operators Gain companion files with all the source code examples PRODUCT SPECS System Requirements Windows 7 and above macOS Important Details Length of access: lifetime Redemption deadline: redeem your code within 30 days of purchase
Access options: desktop mobile Updates included Mercury Learning and Information provides print and digital content in the areas of science and medicine, technology and computing, engineering, and mathematics (STEM disciplines) designed for the professional/reference, trade, library, higher education, career school, and online training markets. Oswald Campesato (San Francisco, CA) specializes in Deep Learning, Data Cleaning, Java, Android, and TensorFlow. He is the author/co-author of over twenty-five books including TensorFlow Pocket Primer; Artificial Intelligence, Machine Learning, and Deep Learning; Android Pocket Primer, Angular4 Pocket Primer, and the Python Pocket Primer (Mercury Learning). Python Basics KEY FEATURES This book is designed for use as a primary introduction to Python and can be used as an introductory text or as a resource for professionals in the industry. The book has been divided into four sections. The first section deals with the language fundamentals, primarily the procedural part of the language, the second introduces the object-oriented paradigms, the third section deals with data structures, and the last is devoted to advanced topics like handling multi-dimensional arrays using NumPy and visualization using Matplotlib. Regular expressions and multi-threading have been introduced in the appendices. Lifetime access on eBooks w/ 450 pages Know more about data structures Gain in-depth treatment of topics such as classes, inheritance,…