
Python 3 Using DeepSeek
Oswald Campesato(Author)
CRC Press
1st Edition
Published on 28. May 2026
Book
Hardback
262 pages
978-1-041-14952-1 (ISBN)
Description
This book is your definitive guide to mastering DeepSeek, a leading open-source Large Language Model (LLM), and leveraging its power through practical Python programming. It is structured to build your expertise from foundational Python data structures and object-oriented programming to advanced model deployment.
The initial chapters establish a strong technical base in Python's core features, including comprehensions, iterators, and the OOP paradigm. The focus then shifts entirely to DeepSeek, detailing its innovative Mixture-of-Experts (MoE) architecture, its superior performance on code-centric benchmarks like HumanEval, and its efficiency advantages. You will gain crucial insight into model management, specifically through the concept of quantization and local deployment with tools like Ollama, which is essential for maximizing performance while minimizing resource usage. The final chapter provides numerous, practical Python mini-projects, allowing you to immediately apply DeepSeek's capabilities to a range of real-world tasks from basic web scraping and data visualization to advanced object-oriented programming and linear regression.
Python 3 Using DeepSeek is essential reading for Python developers (intermediate to advanced), machine learning practitioners, and data scientists. It is your guide to integrating high-performing, open-source LLMs into your workflows, particularly for code generation, algorithmic reasoning, and highly efficient local model deployment.
The initial chapters establish a strong technical base in Python's core features, including comprehensions, iterators, and the OOP paradigm. The focus then shifts entirely to DeepSeek, detailing its innovative Mixture-of-Experts (MoE) architecture, its superior performance on code-centric benchmarks like HumanEval, and its efficiency advantages. You will gain crucial insight into model management, specifically through the concept of quantization and local deployment with tools like Ollama, which is essential for maximizing performance while minimizing resource usage. The final chapter provides numerous, practical Python mini-projects, allowing you to immediately apply DeepSeek's capabilities to a range of real-world tasks from basic web scraping and data visualization to advanced object-oriented programming and linear regression.
Python 3 Using DeepSeek is essential reading for Python developers (intermediate to advanced), machine learning practitioners, and data scientists. It is your guide to integrating high-performing, open-source LLMs into your workflows, particularly for code generation, algorithmic reasoning, and highly efficient local model deployment.
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Professional Practice & Development
Product notice
Laminated cover
Illustrations
2 s/w Zeichnungen, 2 s/w Abbildungen
2 Line drawings, black and white; 2 Illustrations, black and white
Dimensions
Height: 234 mm
Width: 156 mm
Thickness: 16 mm
Weight
562 gr
ISBN-13
978-1-041-14952-1 (9781041149521)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Oswald Campesato
Python 3 Using DeepSeek
E-Book
05/2026
1st Edition
Chapman and Hall
€68.49
Available for download

Oswald Campesato
Python 3 Using DeepSeek
E-Book
05/2026
1st Edition
Chapman and Hall
€68.49
Available for download

Oswald Campesato
Python 3 Using DeepSeek
Book
05/2026
1st Edition
CRC Press
€65.00
Shipment within 15-20 days
Person
Oswald Campesato is a former Lecturer at UC Santa Cruz. He has taught Python courses as well as ML/DL/NLP/RL classes.
Content
1. Data Structures in Python 2. Comprehensions, Iterators, and Generators 3. Regular Expressions 4. Python Custom Classes 5. DeepSeek Introduction 6. Introduction to Quantization 7. DeepSeek and Python Code