*Includes pictures *Includes online resources and a bibliography for further reading *Includes a table of contents Machine learning, in its broadest sense, is a series of methods to recognize and exploit patterns in data. The name comes from the goal of trying to automate (via machines) the process that humans have used to observe the world around them and draw conclusions (i.e. learn) from those observations. Although all practical work in the machine learning field is done through computer programming, the concepts are independent of programming knowledge and instead rely on a mathematical basis. This overview will look only at the conceptual and mathematical side of the field, with little mention of the programming or practical applications. There are a multitude of algorithms that are grouped within the general category of machine learning. Depending on the type of information available, as well as the goal of a problem, many techniques will not work well or simply be impossible to apply. The key to learning different algorithms is to know in which situation each functions best. In many situations there is some sample data from a system and the goal is to interpret this data to define the system or to predict the behavior of new situations. These techniques will be examined later in the overview. Initially, problems will not provide sample data, but instead define a problem according to some constraints; the goal will be to find an optimal solution given the constraints. Machine The History of Automating Computers to Observe and Analyze Data looks at the attempts to develop machine learning, from successes to failures. Along with pictures depicting important people, places, and events, you will learn about machine learning like never before.
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I am happily retired,but having about 35 years as a techie 9 years has proven to short a period to learn how to turn of the curiosity valve. Thanks for the introduction. Now I’ll see if it’s been quenched.
It was interesting to learn about some of the nuts and bolts of training an AI engine, and the pitfalls thereof. Certainly informs the art of engineering, and the artifice that goes into constructing intelligence. 😅