This is a good introductory book to Machine Learning and related topics (Data Analysis, Artificial Intelligence, etc), for those who might want to eventually deepen their technical knowledge of ML, without having to gruel through the details of the methods and algorithms from the get-go。 I...
All chapters have been revised and updated. Introduction to Machine Learning can be used by advanced undergraduates and graduate students who have completed courses in computer programming, probability, calculus, and linear algebra. It will also be of interest to engineers in the field who are ...
All chapters have been revised and updated.Alpayd, EthemMethods Mol BiolAlmeydin E (2014) Introduction to Machine Learning, 3rd ed. Cambridge, MA: MIT Press.E. Alpaydin, Introduction to Machine Learning (2nd Ed). Cambridge, MA: MIT Press, 2010....
This fully revised and expanded text provides a broad and accessible introduction to machine learning for engineering and computer science students. The presentation builds on first principles and geometric intuition, while offering real-world examples, commented implementations in Python, and computational ...
In this new, updated, and expanded edition of Human + Machine , Accenture technology leaders Paul R。 Daugherty and H。 James (Jim) Wilson show that the essence of the AI paradigm shift is the transformation of all business processes within an organization—whether related to breakthrough innova...
A curated list of awesome responsible machine learning resources. - jphall663/awesome-machine-learning-interpretability
Mastering Machine Learning Algorithms, Second Edition helps you harness the real power of machine learning algorithms in order to implement smarter ways of meeting today's overwhelming data needs. This newly updated and revised guide will help you master algorithms used widely in semi-supervised learni...
All chapters have been revised and updated.can be used by advanced undergraduates and graduate students who have completed courses in computer programming, probability, calculus, and linear algebra. It will also be of interest to engineers in the field who are concerned with the application of ...
ADHD is associated with gambling disorder and obesity, showing overlaps of about 20% with each diagnosis. It is important for clinical practice to differentiate between conditions displaying similar symptoms via established diagnostic instruments. Applying the LightGBM algorithm in machine learning, we ...