In data mining, powerful tools like RapidMiner, Python, and R revolutionize how organizations gain valuable insights from large amounts of data. RapidMiner offers a visual interface for designing data workflows, making it ideal for both beginners and advanced practitioners. Python provides an environment for automating and customizing data mining tasks, while R is used for its statistical capabilities and packages for advanced analytics. Together, these tools empower data scientists and analysts to apply machine learning algorithms, statistical models, and data preprocessing techniques efficiently, facilitating deeper understanding and data-driven decision-making across industries. Utilizing RapidMiner, Python, and R for Data Mining Applications explores the integration and application of these three powerful tools in the context of real-world data mining tasks. It delves into the strengths and features of each tool, showcasing how they can be leveraged individually or in combination to handle various stages of the data mining pipeline. This book covers topics such as data clustering, software installation, and programming languages, and is a useful resource for engineers, business owners, academicians, researchers, and data scientists.
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Sarawut Ramjan is a highly accomplished academician with a Ph.D. in Computer and Engineering Management, which he earned from Assumption University in 2013. In 2017, he joined the College of Innovation at Thammasat University as an Associate Professor, where he currently conducts cutting-edge research at the Thammasat University AI Center. Dr. Ramjan is a renowned expert in data science, with a strong focus on teaching and research in this field. His remarkable contributions to the academic world have made him a prominent figure in the academic community.
Jirapon Sunkpho is a distinguished scholar with a passion for academic excellence. He holds a Ph.D. in Civil and Environmental Engineering (Computer-Aided Engineering) from the esteemed Carnegie Mellon University, earned in 2001, as well as an MSc in Applied Data Science and Analytics from Technological University Dublin, which he completed in 2021. Dr. Sunkpho is a visionary leader and currently serves as the Vice Rector in Information Technology at Thammasat University, where he plays a key role in shaping the institution's technological direction. He is also a Board of Director at Airport of Thailand, where his expertise is valued. As an accomplished Associate Professor, Dr. Sunkpho is widely recognized for his teaching excellence and his research in data science. His contributions to this field have been profound, and he remains committed to advancing knowledge in this area. With his unique combination of academic prowess and leadership abilities, Dr. Sunkpho is a true asset to the academic and professional communities.
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Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In data mining, powerful tools like RapidMiner, Python, and R revolutionize how organizations gain valuable insights from large amounts of data. RapidMiner offers a visual interface for designing data workflows, making it ideal for both beginners and advanced practitioners. Python provides an environment for automating and customizing data mining tasks, while R is used for its statistical capabilities and packages for advanced analytics. Together, these tools empower data scientists and analysts to apply machine learning algorithms, statistical models, and data preprocessing techniques efficiently, facilitating deeper understanding and data-driven decision-making across industries. Utilizing RapidMiner, Python, and R for Data Mining Applications explores the integration and application of these three powerful tools in the context of real-world data mining tasks. It delves into the strengths and features of each tool, showcasing how they can be leveraged individually or in combination to handle various stages of the data mining pipeline. This book covers topics such as data clustering, software installation, and programming languages, and is a useful resource for engineers, business owners, academicians, researchers, and data scientists. Seller Inventory # 9798369360019
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