Machine learning in an asynchronous machine

To give a broad view of machine learning, the authors describe the basic methods of learning and give examples of learning systems which illustrate these techniques. Some of the early research in the performance of machine learning systems is discussed. In taking a simplistic approach to machine learning, the techniques are divided into the following categories: rote, inductive, examples, observation and discovery, deduction and analogy. Even by using a simplistic approach these techniques can overlap with each other. High-performance learning machines exhibit more intelligence than low-performance learning machines. Therefore, the performance of a learning algorithm is presented and analyzed with respect to its suitability to a parallel machine environment