Python 3 Using DeepSeek
Seiten
2026
CRC Press (Verlag)
978-1-041-14951-4 (ISBN)
CRC Press (Verlag)
978-1-041-14951-4 (ISBN)
- Noch nicht erschienen (ca. April 2026)
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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.
Oswald Campesato is a Lecturer at UC Santa Cruz. He has taught Python courses as well as ML/DL/NLP/RL classes.
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
| Erscheint lt. Verlag | 15.4.2026 |
|---|---|
| Zusatzinfo | 2 Line drawings, black and white; 2 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Themenwelt | Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge |
| Mathematik / Informatik ► Informatik ► Software Entwicklung | |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| ISBN-10 | 1-041-14951-4 / 1041149514 |
| ISBN-13 | 978-1-041-14951-4 / 9781041149514 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
| Haben Sie eine Frage zum Produkt? |
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