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The Handbook of Data Science and AI

Generate Value from Data with Machine Learning and Data Analytics

Stefan Papp, Wolfgang Weidinger, Katherine Munro, Annalisa Cadonna, Georg Langs (Autoren)

Buch

573 Seiten

2024 | 2nd ed.
Hanser Publications (Verlag)
978-1-56990-934-8 (ISBN)

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Inhaltsverzeichnis (PDF)
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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:

Understand crucial data science concepts, from statistics and mathematics to legal and ethical considerations.
Learn how to build data platforms and deploy safe and robust data projects to production.
Gain the vocabulary to communicate technical requirements and roadmaps to diverse business stakeholders.
Dive into practical case studies that illustrate how knowledge generated from data is changing various industries over the long term.

The team of authors consists of data experts from business and academia, including data scientists, engineers, business leaders and legal experts.

Their broad, deep guide to all aspects of working with data and AI includes:

Machine Learning Fundamentals: Foundations of mathematics and statistics, plus common frameworks for applying ML in practice: from statistical ML to neural networks, Transformers and AutoML
Natural Language Processing and Computer Vision: How to extract valuable insights from text, images and video data, and put it to use in real world applications
Foundation Models and Generative AI: Understand the strengths, challenges, and practical considerations for working with generative models for text, image, video, and other types of data
Modeling and Simulation: Model the behavior of complex systems and do a What-If analysis covering different scenarios
Data Science, ML and AI in production: How can you use cloud and database technologies and MLOps to turn experimentation into a working data product?
Talking about Data: Communication and presentation skills for effective data teams and innovative business leaders
Building Safe, Responsible AI: Best practices in ML Security; safeguarding generative AI models from attack; and how to adhere to GDPR, CCPA, and the new AI act

All authors 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.

Erscheinungsdatum	01.08.2024
Verlagsort	München
Sprache	englisch
Gewicht	1769 g
Einbandart	gebunden
Themenwelt	Mathematik / Informatik ► Informatik ► Datenbanken
Themenwelt	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
Schlagworte	Business Intelligence • Chatbots • computer vision • data analytics • data engineering • Data Scientist • Data strategy • Deep learning • machine learning • ML Ops • ML Security • Statistics
ISBN-10	1-56990-934-2 / 1569909342
ISBN-13	978-1-56990-934-8 / 9781569909348
Zustand	Neuware