Advanced Data Science and Analytics with Python
Jesus Rogel-Salazar(Author)
Chapman and Hall (Publisher)
2nd Edition
Will be published approx. on 25. August 2026
632 pages
E-Book
978-1-040-56010-5 (ISBN)
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for PDF without DRM
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Description
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The second edition of Advanced Data Science and Analytics with Python reflects the rapid transformation of artificial intelligence in recent years. While preserving its practical, modular structure, this edition significantly expands coverage of the techniques shaping modern AI practice.
The deep learning chapter has been substantially broadened to include reinforcement learning and generative adversarial networks, alongside a fully developed exploration of transformer architectures. Generative AI now takes centre stage, with dedicated coverage of self-attention, BERT, GPT, large language model evaluation and API-based interaction. Emerging agentic systems are introduced as part of the evolving AI landscape. Natural language processing has been enhanced with word embeddings, contextual representations and vector search, while network analysis now includes graph representation learning and embedding techniques. The chapter on data product deployment has been strengthened with modern Core ML workflows and new coverage of on-device Foundation Models, bridging experimentation and production.
Fully updated for the contemporary Python ecosystem, this edition equips practitioners with the tools and architectural understanding required to design, build and deploy intelligent systems in today's AI-driven world.
The deep learning chapter has been substantially broadened to include reinforcement learning and generative adversarial networks, alongside a fully developed exploration of transformer architectures. Generative AI now takes centre stage, with dedicated coverage of self-attention, BERT, GPT, large language model evaluation and API-based interaction. Emerging agentic systems are introduced as part of the evolving AI landscape. Natural language processing has been enhanced with word embeddings, contextual representations and vector search, while network analysis now includes graph representation learning and embedding techniques. The chapter on data product deployment has been strengthened with modern Core ML workflows and new coverage of on-device Foundation Models, bridging experimentation and production.
Fully updated for the contemporary Python ecosystem, this edition equips practitioners with the tools and architectural understanding required to design, build and deploy intelligent systems in today's AI-driven world.
More details
Series
Edition
2nd edition
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Illustrations
15 Tables, black and white; 110 Line drawings, black and white; 110 Illustrations, black and white
ISBN-13
978-1-040-56010-5 (9781040560105)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Jesus Rogel-Salazar
Advanced Data Science and Analytics with Python
Book
approx. 08/2026
2nd Edition
CRC Press
€64.50
Not yet published
Jesus Rogel-Salazar
Advanced Data Science and Analytics with Python
Book
approx. 08/2026
2nd Edition
CRC Press
€185.50
Not yet published
Person
Jesus Rogel-Salazar is a lead data scientist, founder of RogueLoop, working for companies such as Ortus Technologies, Tympa Health Technologies, Barclays, AKQA, IBM Data Science Studio and Dow Jones. He is a visiting researcher at the Imperial College Business School, UK and a member of the School of Physics, Astronomy and Mathematics at the University of Hertfordshire, UK.
Content
1. No Time to Lose: Time Series Analysis 2. Speaking Naturally: Text and Natural Language Processing 3. Getting Social: Graph Theory and Social Network Analysis 4. Thinking Deeply: Neural Networks and Deep Learning 5. Attention, Memory and Meaning: A Journey Through Generative AI 6. Here Is One I Made Earlier: Machine Learning Deployment
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