Machine Learning: A Constraint-Based Approach

Amazon.com Price: $99.95 (as of 22/04/2019 22:05 PST- Details)

Categories: , , , , , , , , , , , , ,

Description

Machine Learning: A Constraint-Based Approach provides readers with a refreshing take a look at the basic models and algorithms of machine learning, with an emphasis on current topics of interest that includes neural networks and kernel machines.

The book presents the information in a in point of fact unified manner that may be in keeping with the notion of learning from environmental constraints. Even as regarding symbolic knowledge bases as a choice of constraints, the book draws a path towards a deep integration with machine learning that will depend on the idea of adopting multivalued logic formalisms, like in fuzzy systems. A special attention is reserved to deep learning, which nicely fits the constrained- based approach followed in this book.

This book presents a simpler unified notion of regularization, which is strictly connected with the parsimony principle, and includes many solved exercises that are classified in keeping with the Donald Knuth ranking of difficulty, which essentially consists of a mixture of warm-up exercises that lead to deeper research problems. A software simulator may be included.

  • Presents fundamental machine learning concepts, such as neural networks and kernel machines in a unified manner
  • Provides in-depth coverage of unsupervised and semi-supervised learning
  • Includes a software simulator for kernel machines and learning from constraints that also includes exercises to facilitate learning
  • Contains 250 solved examples and exercises chosen particularly for their progression of difficulty from simple to complex

Related products

Home » Shop » Books » Specialty Boutique » New, Used and Rental Textbooks » Computer Science » AI and Machine Learning » Computer Vision and Pattern Recognition » Machine Learning: A Constraint-Based Approach

Recent Products