 Bayesian Reasoning and Machine Learning
We live in a world that is rich in data, ever increasing in scale. This data comes from many di erent
sources in science (bioinformatics, astronomy, physics, environmental monitoring) and commerce (customer
databases, nancial transactions, engine monitoring, speech recognition, surveillance, search). Possessing
the knowledge as to... | | Learning in Embedded Systems (Bradford Books)
Learning to perform complex action strategies is an important problem in the fields of artificial intelligence, robotics, and machine learning. Filled with interesting new experimental results, Learning in Embedded Systems explores algorithms that learn efficiently from trial-and error experience with an external world. It is the first... | | Introduction to Machine Learning (Adaptive Computation and Machine Learning)The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, recognize faces or spoken speech, optimize robot behavior so that a task can be completed... |
