THE OBJECT ORIENTED APPROACH TO PROBLEM SOLVING AND MACHINE LEARNING WITH PYTHON (PB 2025). Este artículo no está disponible.
Idioma: inglés
Editorial: TAYLOR & FRANCIS NP EXCLUSIVE(CBS), 2025
- Tapa blanda
- Nuevo

Librería: UK BOOKS STORE, London, London, Reino UnidoUK BOOKS STORE
Vendedor de IberLibro desde 11 de marzo de 2024
Condición: Nuevo
EUR 128,37
Descripción del artículo del vendedor
Brand New ! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
N° de ref. del artículo Cvs 9781032668314
- Título
- THE OBJECT ORIENTED APPROACH TO PROBLEM SOLVING AND MACHINE LEARNING WITH PYTHON (PB 2025)
- Autor
- MATHEW S S
- Editorial
- TAYLOR & FRANCIS NP EXCLUSIVE(CBS)
- Año de publicación
- 2025
- Estado
- New
- Encuadernación
- Encuadernación de tapa blanda
- Idioma
- inglés
- ISBN 10
- 1032668318
- ISBN 13
- 9781032668314
- Edición
- Edición Internacional
This book is a comprehensive guide suitable for beginners and experienced developers alike. It teaches readers how to master object-oriented programming (OOP) with Python and use it in real-world applications.
Start by solidifying your OOP foundation with clear explanations of core concepts such as use cases and class diagrams. This book goes beyond theory as you get practical examples with well-documented source code available in the book and on GitHub.
This book doesn’t stop at the basics. Explore how OOP empowers fields such as data persistence, graphical user interfaces (GUIs), machine learning, and data science, including social media analysis. Learn about machine learning algorithms for classification, regression, and unsupervised learning, putting you at the forefront of AI innovation.
Each chapter is designed for hands-on learning. You’ll solidify your understanding with case studies, exercises, and projects that apply your newfound knowledge to real-world scenarios. The progressive structure ensures mastery, with each chapter building on the previous one, reinforced by exercises and projects.
Numerous code examples and access to the source code enhance your learning experience. This book is your one-stop shop for mastering OOP with Python and venturing into the exciting world of machine learning and data science.
“Sinopsis” puede pertenecer a otra edición de este título.
Acerca del autor
Sujith Samuel Mathew holds a PhD in computer science from the University of Adelaide, Australia. He is an associate professor at Zayed University, UAE. He specializes in ubiquitous and distributed computing, focusing on the Internet of Things and related Smart City applications.
Mohammad Amin Kuhail holds an MSc in software engineering from the University of York and a PhD in software development from IT University of Copenhagen. He is an associate professor at Zayed University, specializing in human–computer interaction and software engineering, and he researches chatbot technology, user behavior, and education.
Maha Hadid holds an MSc in Information Sciences and Systems from the University of Marseille in France. She is an instructor at Zayed University, UAE, with experience in undergraduate courses and instructional design and delivery for blended and classroom-based courses.
Shahbano Farooq holds an MSc in computer science from the University of Calgary. She is an instructor at Zayed University, UAE, specializing in human-computer interaction and machine learning.
“Acerca de” puede pertenecer a otra edición de este título.