Data Mining and Machine Learning Applications

The book discusses the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines. It covers classification and clustering methods, regression and classification, and clustering to find accurate results. Applications include fraud detection, image processing, medical diagnosis, weather prediction, e-commerce, and more.

Format: Hardback
Length: 496 pages
Publication date: 25 February 2022
Publisher: John Wiley & Sons Inc

The book delves into the intricate realm of data mining and machine learning, shedding light on the pressing demands of these fields and fostering a deeper understanding among researchers from diverse disciplines. By promoting collaboration, it plays a pivotal role in advancing research development and fostering innovation.

In today's digital age, data has emerged as the most valuable currency, surpassing even gold in its significance. Within this new realm of data, data analytics and machine learning stand as the most captivating jewels. These interdisciplinary fields intertwine to unlock the immense potential hidden within vast datasets.

Data mining, a subset of data analytics, employs algorithms that undergo continuous improvement through exposure to data. These algorithms, driven by the power of machine learning, learn from patterns and insights, enabling them to make accurate predictions and decisions. By leveraging classification and clustering methods, massive datasets can be organized and analyzed, yielding precise results.

Common technologies employed in this process include support vector machines and neural networks, which employ forward and backward propagation to refine their accuracy. These algorithms are applied across a wide range of applications, including fraud detection, image processing, medical diagnosis, weather prediction, e-commerce, and more.

The book offers a comprehensive review of the state-of-the-art in data mining and machine learning, providing insights into the latest techniques and methodologies. It also explores the learning methods employed in human-computer interaction, emphasizing their role in designing and implementing applications that meet the evolving needs of modern and real-time systems.

Furthermore, the book delves into implementation strategies and future research directions, ensuring that data mining and machine learning strategies are tailored to meet the design and application requirements of diverse industries. It discusses real-time problems and their implications, offering valuable perspectives to industry and academic researchers, scientists, engineers, and practitioners in the fields of information technology, data science, machine learning, and deep learning.

With its extensive coverage and insightful discussions, this book serves as a valuable resource for anyone seeking to delve into the world of data mining and machine learning. It equips readers with the knowledge and tools necessary to unlock the full potential of data and drive innovation in various domains.

Weight: 812g
Dimension: 233 x 160 x 31 (mm)
ISBN-13: 9781119791782