This book provides a comprehensive introduction to Machine Learning, covering both fundamental concepts and advanced techniques. It begins with the basics of machine learning, including supervised, unsupervised, and reinforcement learning, followed by the mathematical foundations such as linear algebra, probability, statistics, calculus, and information theory. The book then explores key machine learning algorithms including regression, classification, clustering, ensemble learning, neural networks, deep learning, CNNs, RNNs, transformers, large language models, GANs, diffusion models, reinforcement learning, and graph neural networks.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Dr. Rajendra M. Rewatkar,.is an Associate Professor and Vice Dean (Research) in the Faculty of Engineering and Technology, Datta Meghe Institute of Higher Education and Research (DMIHER), Sawangi (Meghe), Wardha, India. He also serves as the Head of the Department and PhD Convener.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes Königreich
PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000. Bestandsnummer des Verkäufers L2-9786630120288
Anzahl: Mehr als 20 verfügbar
Anbieter: Grand Eagle Retail, Bensenville, IL, USA
Paperback. Zustand: new. Paperback. This book provides a comprehensive introduction to Machine Learning, covering both fundamental concepts and advanced techniques. It begins with the basics of machine learning, including supervised, unsupervised, and reinforcement learning, followed by the mathematical foundations such as linear algebra, probability, statistics, calculus, and information theory. The book then explores key machine learning algorithms including regression, classification, clustering, ensemble learning, neural networks, deep learning, CNNs, RNNs, transformers, large language models, GANs, diffusion models, reinforcement learning, and graph neural networks. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9786630120288
Anbieter: California Books, Miami, FL, USA
Zustand: New. Bestandsnummer des Verkäufers I-9786630120288
Anzahl: Mehr als 20 verfügbar
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 152 pp. Englisch. Bestandsnummer des Verkäufers 9786630120288
Anzahl: 2 verfügbar
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book provides a comprehensive introduction to Machine Learning, covering both fundamental concepts and advanced techniques. It begins with the basics of machine learning, including supervised, unsupervised, and reinforcement learning, followed by the mathematical foundations such as linear algebra, probability, statistics, calculus, and information theory. The book then explores key machine learning algorithms including regression, classification, clustering, ensemble learning, neural networks, deep learning, CNNs, RNNs, transformers, large language models, GANs, diffusion models, reinforcement learning, and graph neural networks. Bestandsnummer des Verkäufers 9786630120288
Anzahl: 2 verfügbar
Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. MACHINE LEARNING Foundations, Algorithms, and Applications | Rajendra Motiramji Rewatkar (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786630120288 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Bestandsnummer des Verkäufers 136373081
Anzahl: 5 verfügbar
Anbieter: CitiRetail, Stevenage, Vereinigtes Königreich
Paperback. Zustand: new. Paperback. This book provides a comprehensive introduction to Machine Learning, covering both fundamental concepts and advanced techniques. It begins with the basics of machine learning, including supervised, unsupervised, and reinforcement learning, followed by the mathematical foundations such as linear algebra, probability, statistics, calculus, and information theory. The book then explores key machine learning algorithms including regression, classification, clustering, ensemble learning, neural networks, deep learning, CNNs, RNNs, transformers, large language models, GANs, diffusion models, reinforcement learning, and graph neural networks. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9786630120288
Anzahl: 1 verfügbar