9781107077232 - Mining of Massive Datasets

Mining of Massive Datasets

'Mining of Massive Datasets' by Anand Rajaraman is a comprehensive guide that delves into the complexities of handling and extracting valuable information from large datasets. This book is a must-read for data scientists, engineers, and anyone interested in the field of big data. It covers a wide range of topics including data mining algorithms, machine learning techniques, and the practical applications of these methods in real-world scenarios. The author provides a detailed explanation of how to process and analyze data at scale, making it accessible to readers with a basic understanding of computer science and statistics. With its clear examples and practical advice, this book serves as an invaluable resource for professionals looking to enhance their skills in data mining and analysis.

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€22.95
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Auteur Anand Rajaraman
ISBN 9781107077232
Taal en
Bindwijze Hardcover
Tags data mining big data machine learning data science Anand Rajaraman

'Mining of Massive Datasets' offers an in-depth look at the challenges and solutions associated with big data. Anand Rajaraman's expertise shines through in his ability to break down complex concepts into understandable segments. The book's strengths lie in its practical approach, offering readers actionable insights into data mining techniques. However, some readers may find the technical depth daunting without prior knowledge in the field. Despite this, the book's comprehensive coverage of topics such as recommendation systems, clustering, and classification makes it a standout resource. The inclusion of real-world examples further enhances its value, providing context for the theoretical concepts discussed.

In 'Mining of Massive Datasets', Anand Rajaraman explores the vast and intricate world of big data, offering readers a roadmap to navigating its challenges. The book begins with an introduction to the fundamentals of data mining, gradually progressing to more advanced topics like scalable algorithms and data stream processing. Rajaraman meticulously explains each concept, ensuring readers grasp the underlying principles before moving forward. Key chapters focus on the application of data mining in areas such as social networks and web search, illustrating the practical implications of these technologies. The book concludes with a forward-looking perspective on the future of big data, encouraging readers to think critically about its evolving landscape. This summary encapsulates the book's essence, highlighting its role as a pivotal guide in the field of data science.