Advanced Data Science and Analytics with Python

2. Auflage 2026
ISBN: 978-1-041-10360-8
Verlag: Taylor & Francis

Buch, Englisch, 632 Seiten, Format (B × H): 191 mm x 235 mm

Reihe: Chapman & Hall/CRC Data Mining and Knowledge Discovery Series

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.

Zielgruppe

Professional Practice & Development

Autoren/Hrsg.

Rogel-Salazar, Jesús

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Spiele-Programmierung, Rendering, Animation
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Wirtschaftsstatistik, Demographie
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining

Inhaltsverzeichnis

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

Über Autor(innen)

Jesús 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.