Practical Machine Learning Illustrated with KNIME by Yu Geng (.PDF)
File Size: 37.5 MB
Practical Machine Learning Illustrated with KNIME by Yu Geng, Qin Li, Geng Yang, Wan Qiu
Requirements: .PDF reader, 37.5 MB
Overview: This book guides professionals and students from various backgrounds to use Machine Learning in their own fields with low-code platform KNIME and without coding. Many people from various industries need use Machine Learning to solve problems in their own domains. However, Machine Learning is often viewed as the domain of programmers, especially for those who are familiar with Python. It is too hard for people from different backgrounds to learn Python to use Machine Learning. KNIME, the low-code platform, comes to help. KNIME helps people use Machine Learning in an intuitive environment, enabling everyone to focus on what to do instead of how to do. This book helps the readers gain an intuitive understanding of the basic concepts of Machine Learning through illustrations to practice Machine Learning in their respective fields. The author provides a practical guide on how to participate in Kaggle completions with KNIME to practice Machine Learning techniques. This textbook aims to provide a comprehensive and accessible introduction to AI and ML. It is structured into three parts: Introduction to AI Technology, Traditional Machine Learning, and Deep Learning. The first part lays the groundwork of essential knowledge, the second part explores various ML models and techniques, and the concluding part introduces the basics of Deep Learning. Primarily crafted for beginners, this textbook is also a valuable resource for anyone interested in the practical applications of AI and ML. Our aspiration is that readers will, in the spirit of Caesar’s renowned quote, “Veni Vidi Vici,” truly come, see, and conquer the basics of ML.
Genre: Non-Fiction > Tech & Devices
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