machine deep learning solutions (17 Ergebnisse)

Paperback. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Zustand: Good. Former library book; may include library markings. Used book that is in clean, average condition without any missing pages.

Zustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,750grams, ISBN:9781491989388.

Zustand: Very good.

Zustand: New.

Zustand: Gut. 349 S. - Wir versenden aus unserem deutschen Lager heraus in plastikfreien oder wiederverwendeten Polstertaschen. Sprache: Englisch Gewicht in Gramm: 666 Taschenbuch, Maße: 17.15 cm x 1.91 cm x 22.86 cm.

Zustand: New. 2023. 2nd Edition. Paperback. . . . . . Books ship from the US and Ireland.

Paperback. Zustand: Brand New. 56 pages. 9.25x6.10x0.12 inches. In Stock.

Paperback. Zustand: Brand New. 2nd edition. 380 pages. 9.19x7.00x0.85 inches. In Stock.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This SpringerBrief presents the underlying principles of machine learning and how to deploy various deep learning tools and techniques to tackle and solve certain challenges facing the cybersecurity industry.By implementing innovative deep learning solutions, cybersecurity researchers, students and practitioners can analyze patterns and learn how to prevent cyber-attacks and respond to changing malware behavior.The knowledge and tools introduced in this brief can also assist cybersecurity teams to become more proactive in preventing threats and responding to active attacks in real time. It can reduce the amount of time spent on routinetasks and enable organizations to use their resources more strategically. In short, the knowledge and techniques provided in this brief can help make cybersecurity simpler, more proactive, less expensive and far more effectiveAdvanced-level students in computer science studying machine learning with a cybersecurity focus will find this SpringerBrief useful as a study guide. Researchers and cybersecurity professionals focusing on the applicationof machine learning tools and techniques to the cybersecurity domain will also want to purchase this SpringerBrief.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 112 | Sprache: Englisch | Produktart: Bücher | Machine Learning for Absolute Beginners" is a book designed to introduce readers with no prior experience to the exciting and rapidly growing field of machine learning. Machine learning is a branch of artificial intelligence that enables computers to learn from data and make predictions or decisions based on that learning.This book is written in a clear and approachable style, making it easy for readers to understand the core concepts and techniques of machine learning. It assumes no prior knowledge of the subject, and starts from the very basics, gradually building up the reader's understanding of the field.The book covers a wide range of topics, including data preprocessing, classification, regression, clustering, and deep learning. It also includes practical examples and hands-on exercises that allow readers to apply what they've learned and gain real-world experience in machine learning.Whether you are a student, a professional, or just someone interested in learning about machine learning, this book provides a solid foundation for understanding the fundamentals of this exciting field. By the end of the book, readers will have a strong understanding of the concepts and techniques of machine learning and will be well-equipped to tackle more advanced topics in the future.

Taschenbuch. Zustand: Neu. Neuware - This practical guide provides more than 200 self-contained recipes to help you solve machine learning challenges you may encounter in your work. If you're comfortable with Python and its libraries, including pandas and scikit-learn, you'll be able to address specific problems, from loading data to training models and leveraging neural networks.

Taschenbuch. Zustand: Neu. Machine Learning with Python Cookbook | Practical Solutions from Preprocessing to Deep Learning | Kyle Gallatin (u. a.) | Taschenbuch | Englisch | 2023 | O'Reilly Media | EAN 9781098135720 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Shallow Learning vs. Deep Learning | A Practical Guide for Machine Learning Solutions | Ömer Faruk Ertu¿rul (u. a.) | Taschenbuch | xii | Englisch | 2025 | Springer | EAN 9783031695018 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book explores the ongoing debate between shallow and deep learning in the field of machine learning. It provides a comprehensive survey of machine learning methods, from shallow learning to deep learning, and examines their applications across various domains. Shallow Learning vs Deep Learning: A Practical Guide for Machine Learning Solutions emphasizes that the choice of a machine learning approach should be informed by the specific characteristics of the dataset, the operational environment, and the unique requirements of each application, rather than being influenced by prevailing trends.In each chapter, the book delves into different application areas, such as engineering, real-world scenarios, social applications, image processing, biomedical applications, anomaly detection, natural language processing, speech recognition, recommendation systems, autonomous systems, and smart grid applications. By comparing and contrasting the effectiveness of shallow and deep learning in these areas, the book provides a framework for thoughtful selection and application of machine learning strategies. This guide is designed for researchers, practitioners, and students who seek to deepen their understanding of when and how to apply different machine learning techniques effectively. Through comparative studies and detailed analyses, readers will gain valuable insights to make informed decisions in their respective fields.

Hardcover. Zustand: Brand New. 287 pages. 9.25x6.10x9.21 inches. In Stock.