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The Handbook of Data Science and AI

Katherine Munro, Stefan Papp, Zoltan Toth, Wolfgang Weidinger, Danko Nikolic, Barbora Antosova Vesela, Karin Bruckmüller, Annalisa Cadonna, Jana Eder, Jeannette Gorzala, Gerald A. Hahn, Georg Langs, Roxane Licandro, Christian Mata, Sean McIntyre, Mario Meir-Huber, György Móra, Manuel Pasieska, Victoria Rugli, Rania Wazir, Günther Zauner (Gebundene Ausgabe, Englisch)

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Beschreibung

- 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. WHAT‘S 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. Weniger zeigen

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Produktinformationen

Technische Daten

Erscheinungsdatum

09.08.2024

Sprache

Englisch

EAN

9781569909348

Herausgeber

Hanser Publications

Sonderedition

Nein

Autor

Katherine Munro, Stefan Papp, Zoltan Toth, Wolfgang Weidinger, Danko Nikolic, Barbora Antosova Vesela, Karin Bruckmüller, Annalisa Cadonna, Jana Eder, Jeannette Gorzala, Gerald A. Hahn, Georg Langs, Roxane Licandro, Christian Mata, Sean McIntyre, Mario Meir-Huber, György Móra, Manuel Pasieska, Victoria Rugli, Rania Wazir, Günther Zauner

Seitenanzahl

876

Auflage

Einbandart

Gebundene Ausgabe

Buch Untertitel

Generate Value from Data with Machine Learning and Data Analytics

Schlagwörter

Business Intelligence, Chatbots, Computer Vision, Data Analytics, Data Engineering, Data Scientist, Data Strategy, Deep Learning, Machine Learning, ML Ops, ML Security, Statistics

Thema-Inhalt

UN - Datenbanken GPH - Datenwissenschaft und -analyse: allgemein LNQD - Datenschutzrecht UMT - Datenbankprogrammierung UYQM - Maschinelles Lernen

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