Semi-Supervised Learning (Adaptive Computation and Machine Learning) In the field of machine learning, semi-supervised learning (SSL) occupies the middle ground, between supervised learning (in which all training examples are labeled) and unsupervised learning (in which no label data are given). Interest in SSL has increased in recent years, particularly because of application domains in which unlabeled data are... Design Concepts in Programming Languages This book is the text for 6.821 Programming Languages, an entry-level, singlesemester, graduate-level course at the Massachusetts Institute of Technology. The students that take our course know how to program and are mathematically inclined, but they typically have not had an introduction to programming language design or its mathematical...
Rules of Play: Game Design Fundamentals
For hundreds of years, the field of game design has drifted along under the radar of culture, producing
timeless masterpieces and masterful time-wasters without drawing much attention to itself-without, in fact,
behaving like a "field" at all. Suddenly, powered by the big bang of computer technology, game design has... 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...
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