Machine Learning and Data Mining Annual Volume 2023 - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Machine Learning and Data Mining Annual Volume 2023 write by . This book was released on 2023-12-13. Machine Learning and Data Mining Annual Volume 2023 available in PDF, EPUB and Kindle. The interest within the academic community regarding AI has experienced exponential growth in recent years. Several key factors have contributed to this surge in interest. Firstly, the rapid advancements in AI technologies have showcased their potential to revolutionize various fields, such as healthcare, finance, and transportation, sparking curiosity and enthusiasm among researchers and scholars. Secondly, the availability of vast amounts of data and computing power has enabled academics to delve deeper into AI research, exploring complex algorithms and models to tackle real-world problems. Additionally, the interdisciplinary nature of AI has encouraged collaboration among experts from diverse fields like computer science, neuroscience, psychology, and ethics, fostering a rich exchange of ideas and approaches. With contributions from a diverse group of authors, this book offers a multifaceted perspective on machine learning and data mining. Whether you’re an experienced researcher or a newcomer, this collection is an essential resource for staying at the forefront of these dynamic and influential disciplines.
Data Mining and Big Data
Data Mining and Big Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Mining and Big Data write by Ying Tan. This book was released on . Data Mining and Big Data available in PDF, EPUB and Kindle.
Machine Learning for Data Science Handbook
Machine Learning for Data Science Handbook - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Machine Learning for Data Science Handbook write by Lior Rokach. This book was released on 2023-08-17. Machine Learning for Data Science Handbook available in PDF, EPUB and Kindle. This book organizes key concepts, theories, standards, methodologies, trends, challenges and applications of data mining and knowledge discovery in databases. It first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. It also gives in-depth descriptions of data mining applications in various interdisciplinary industries.
Introduction to machine learning and data mining - lecture notes, Fall 2023, version 1.0
Introduction to machine learning and data mining - lecture notes, Fall 2023, version 1.0 - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Introduction to machine learning and data mining - lecture notes, Fall 2023, version 1.0 write by . This book was released on . Introduction to machine learning and data mining - lecture notes, Fall 2023, version 1.0 available in PDF, EPUB and Kindle.
Data Mining and Machine Learning Applications
Data Mining and Machine Learning Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Mining and Machine Learning Applications write by Rohit Raja. This book was released on 2022-01-26. Data Mining and Machine Learning Applications available in PDF, EPUB and Kindle. DATA MINING AND MACHINE LEARNING APPLICATIONS The book elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines, thus facilitating research development and collaboration. Data, the latest currency of today’s world, is the new gold. In this new form of gold, the most beautiful jewels are data analytics and machine learning. Data mining and machine learning are considered interdisciplinary fields. Data mining is a subset of data analytics and machine learning involves the use of algorithms that automatically improve through experience based on data. Massive datasets can be classified and clustered to obtain accurate results. The most common technologies used include classification and clustering methods. Accuracy and error rates are calculated for regression and classification and clustering to find actual results through algorithms like support vector machines and neural networks with forward and backward propagation. Applications include fraud detection, image processing, medical diagnosis, weather prediction, e-commerce and so forth. The book features: A review of the state-of-the-art in data mining and machine learning, A review and description of the learning methods in human-computer interaction, Implementation strategies and future research directions used to meet the design and application requirements of several modern and real-time applications for a long time, The scope and implementation of a majority of data mining and machine learning strategies. A discussion of real-time problems. Audience Industry and academic researchers, scientists, and engineers in information technology, data science and machine and deep learning, as well as artificial intelligence more broadly.
