TL
TL;DR
ML has be applied to many real-world problems or tasks, like medical diagno sis, robotics, recommendation systems, facial recognition, stock prices prediction, and sentiment analysis, with great success.
Abstract
coined in 1959 by Arthur Samuel [Samuel 1959], Tom Mitchell [Mitchell 1997] provided a more formal definition: “A computer program is said to learn from experience E with respect to some task T and some performance measure P, if its performance on T, as measured by P, improves with experience E.” ML has be applied to many real-world problems or tasks, like medical diagno sis, robotics, recommendation systems, facial recognition, stock prices prediction, and sentiment analysis, with great success. We can divide ML algorithms into three main categories (see Figure 4.1): Machine Learning Basics