
The Handbook of Data Science and AI
Generate Value from Data with Machine Learning and Data Analytics
Katherine MunroStefan PappZoltan TothWolfgang WeidingerDanko NikolicBarbora Antosova VeselaKarin BruckmüllerAnnalisa CadonnaJana EderJeannette GorzalaGerald A. HahnGeorg LangsRoxane LicandroChristian MataSean McIntyreMario Meir-HuberGyörgy MóraManuel PasieskaVictoria RugliRania WazirGünther Zauner(Author)
Hanser Publications (Publisher)
2nd Edition
Published on 16. August 2024
Book
Hardback
876 pages
978-1-56990-934-8 (ISBN)
Shipment within 3-4 weeks
Description
- A comprehensive overview of the various fields of application of data science and artificial intelligence.
- Case studies from practice to make the described concepts tangible.
- Practical examples to help you carry out simple data analysis projects.
- BONUS in print edition: E-Book inside
Data Science, Big Data, Artificial Intelligence and Generative AI are currently some of the most talked-about concepts in industry, government, and society, and yet also the most misunderstood. This book will clarify these concepts and provide you with practical knowledge to apply them.
Using exercises and real-world examples, it will show you how to apply data science methods, build data platforms, and deploy data- and ML-driven projects to production. It will help you understand - and explain to various stakeholders - how to generate value from such endeavors. Along the way, it will bring essential data science concepts to life, including statistics, mathematics, and machine learning fundamentals, and explore crucial topics like critical thinking, legal and ethical considerations, and building high-performing data teams.
Readers of all levels of data familiarity - from aspiring data scientists to expert engineers to data leaders - will ultimately learn: how can an organization become more data-driven, what challenges might it face, and how can they as individuals help make that journey a success.
The team of authors consists of data professionals from business and academia, including data scientists, engineers, business leaders and legal experts. All are members of the Vienna Data Science Group (VDSG), an NGO that aims to establish a platform for exchanging knowledge on the application of data science, AI and machine learning, and raising awareness of the opportunities and potential risks of these technologies.
WHATS INSIDE //
- Critical Thinking and Data Culture: How evidence driven decision making is the base for effective AI.
- Machine Learning Fundamentals: Foundations of mathematics, statistics, and ML algorithms and architectures
- Natural Language Processing and Computer Vision: How to extract valuable insights from text, images and video data, for real world applications.
- Foundation Models and Generative AI: Understand the strengths and challenges of generative models for text, images, video, and more.
- ML and AI in Production: Turning experimentation into a working data science product.
- Presenting your Results: Essential presentation techniques for data scientists.
Reviews / Votes
"Die Neuauflage zeichnet sich durch ihre Aktualität aus, indem sie die neuesten Entwicklungen und Trends berücksichtigt. Trotz der Komplexität der Themen ist das Buch verständlich geschrieben und eignet sich sowohl für Einsteiger als auch für erfahrene Praktiker. Es verbindet theoretische Grundlagen mit praktischen Anwendungen und legt Wert auf Interdisziplinarität, indem es Konzepte aus verschiedenen Fachbereichen verknüpft und viele Beispiele aus der realen Welt liefert. Damit ist das Handbuch eine wertvolle Ressource für Leser, die ihr Wissen im Bereich Data Science und KI vertiefen oder erweitern möchten, und ein unverzichtbares Werk für alle, die sich professionell mit Data Science und KI beschäftigen. Für Dezember 2024 plant der Verlag eine erweiterte deutschsprachige Neuauflage des Handbuchs." dotnetrpro, November 2024More details
Edition
2., aktualisierte und erweiterte Auflage
Language
English
Place of publication
München
Germany
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 24.5 cm
Width: 18.5 cm
Thickness: 5.8 cm
Weight
1730 gr
ISBN-13
978-1-56990-934-8 (9781569909348)
Schweitzer Classification
Other editions
New editions

Stefan Papp | Zoltan Toth | Katherine Munro
The Handbook of Data Science and AI
Generate Value from Data with Machine Learning and Data Analytics
Book
04/2026
3rd Edition
Hanser Publications
€99.99
Available immediately
Persons
Author
Katherine Munro is a Data Scientist, Data Science Ambassador and Computational Linguist, conducting research and development and corporate training in AI, Natural Language Processing and Data Science. Katherine began her tech career specializing in user interfaces and Natural Language Understanding, with roles at Mercedes-Benz and the Fraunhofer Institute. Currently she is building smart conversational AI systems using NLP techniques and Large Language Models.
Stefan Papp is an entrepreneur who works with Fortune 500 companies to build data platforms and helps them to become more data-driven. Living with his family in Armenia, he is also involved in the Armenian startup ecosystem, and he acts there as an advisor and investor.
Zoltan C. Toth is a data engineering architect, lecturer and entrepreneur. With a background in Computer Science and Mathematics, he has taught data architectures, big data technologies and machine learning operations to Fortune 500 companies worldwide. In the past two decades he has worked with several large enterprises as a Solutions Architect, implementing data analytics infrastructures and scaling them up to processing petabytes of data.
Wolfgang Weidinger is a Data Scientist and AI professional. He has worked in a wide variety of industries and sectors such as start-ups, finance, consulting, wholesale and insurance. There he led Data Science & AI teams and drove their role as spearheads in digital and data-driven transformation. He is President of the Vienna Data Science Group (www.vdsg.at), a non-profit association of and for Data Scientists and all other Data & AI professionals.
ISNI: 0000 0005 1568 2160
ISNI: 0000 0005 1568 2160
Dr. Danko Nikolic is an expert in both brain research and AI. For many years he has run an electrophysiology lab at the Max-Planck Institute for Brain Research. Also, he is an AI and machine learning professional heading a Data Science team and developing commercial solutions based on AI technology.
ISNI: 0000 0005 1554 5107
ISNI: 0000 0003 8839 1001
ISNI: 0000 0005 1590 0711
ISNI: 0000 0001 0712 7467