The book provides a structured introduction to core areas of artificial intelligence, including machine learning, deep learning, large language models, and agent-based systems. It combines theoretical foundations with practical implementation, using tools such as scikit-learn, Keras, and Ollama. Each chapter includes code examples, exercises, and links to interactive notebooks. The focus lies on conveying applicable knowledge for real-world use. The book is intended for students and practitioners in computer science or related fields and can be used for teaching, self-study, or reference in applied contexts.
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Oliver Kramer is Professor of Computational Intelligence at the University of Oldenburg, Germany. His research focuses on evolutionary computation, machine learning, and large language model–based cognitive architectures, with applications in optimization, bioinformatics, and artificial general intelligence. He has authored numerous books and articles and has presented his work at leading conferences such as GECCO, CEC, and ESANN. His interdisciplinary projects explore connections between AI, biology, and cognitive science.
The book provides a structured introduction to core areas of artificial intelligence, including machine learning, deep learning, large language models, and agent-based systems. It combines theoretical foundations with practical implementation, using tools such as scikit-learn, Keras, and Ollama. Each chapter includes code examples, exercises, and links to interactive notebooks. The focus lies on conveying applicable knowledge for real-world use. The book is intended for students and practitioners in computer science or related fields and can be used for teaching, self-study, or reference in applied contexts.
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Hardcover. Condición: new. Hardcover. The book provides a structured introduction to core areas of artificial intelligence, including machine learning, deep learning, large language models, and agent-based systems. It combines theoretical foundations with practical implementation, using tools such as scikit-learn, Keras, and Ollama. Each chapter includes code examples, exercises, and links to interactive notebooks. The focus lies on conveying applicable knowledge for real-world use. The book is intended for students and practitioners in computer science or related fields and can be used for teaching, self-study, or reference in applied contexts. The book provides a structured introduction to core areas of artificial intelligence, including machine learning, deep learning, large language models, and agent-based systems. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9783032066367
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book provides a structured introduction to core areas of artificial intelligence, including machine learning, deep learning, large language models, and agent-based systems. It combines theoretical foundations with practical implementation, using tools such as scikit-learn, Keras, and Ollama. Each chapter includes code examples, exercises, and links to interactive not Elektronisches Buch. The focus lies on conveying applicable knowledge for real-world use. The book is intended for students and practitioners in computer science or related fields and can be used for teaching, self-study, or reference in applied contexts. 82 pp. Englisch. Nº de ref. del artículo: 9783032066367
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - The book provides a structured introduction to core areas of artificial intelligence, including machine learning, deep learning, large language models, and agent-based systems. It combines theoretical foundations with practical implementation, using tools such as scikit-learn, Keras, and Ollama. Each chapter includes code examples, exercises, and links to interactive not Elektronisches Buch. The focus lies on conveying applicable knowledge for real-world use. The book is intended for students and practitioners in computer science or related fields and can be used for teaching, self-study, or reference in applied contexts. Nº de ref. del artículo: 9783032066367
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Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book provides a structured introduction to core areas of artificial intelligence, including machine learning, deep learning, large language models, and agent-based systems. It combines theoretical foundations with practical implementation, using tools such as scikit-learn, Keras, and Ollama. Each chapter includes code examples, exercises, and links to interactive not Elektronisches Buch. The focus lies on conveying applicable knowledge for real-world use. The book is intended for students and practitioners in computer science or related fields and can be used for teaching, self-study, or reference in applied contexts.Springer Nature Customer Service Center GmbH, Europaplatz 3,69115 Heidelberg, Germany, Heidelberg 92 pp. Englisch. Nº de ref. del artículo: 9783032066367
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