Data mining is the art of extracting of synthetic high-level information from a large quantity of low-level information. As an example, a company selling books on Internet has a lot of customer’s profiles. Data mining techniques can help to find groups of similar customer’s profiles. Another example is air quality measurement. A lot of sensors are spread through the city, measuring all sorts of data. Data mining mechanics can help to sump-up all those data into a simple model, allowing predictions. Data mining, although a relatively young computer science field is now commonly used in industry. Data mining is a key technology used by many other advanced techniques, such as search engines, voice and image recognition, etc. This course is a practical introduction to data mining. Basic concepts and algorithms for data mining are introduced through simple but concrete examples. The teaching will focus more on the practical aspects, how to effectively use such techniques. We will just give the intuition behind each introduced idea, without going deeply in the theoretical foundations. Some basic knowledge about statistics will be introduced as well. |
