The only requirement to solve practical problems using mathematical tools probably know a little knowledge of probability and programming. The Bayesian approach is a common mathematical method using probabilistic knowledge to solve the problem of uncertainty, for a computer professional who should be familiar with its use, such as machine translation, a common computer speech recognition, spam detection, etc. problem areas.
We discuss how to solve practical problems in more than a dozen real-life space in a total of 15 chapters. In the process of resolving these problems, but also help create subtle modeling decision-making methodology, numerical modeling errors and error how to choose, how to mathematically model the specific issues, how to seize the main contradiction in question (the key parameters of the model ), and then step by step to optimize or verify the validity or the limitations of the model. In this sense, it is a successful sample on mathematical modeling.
Learning Reference:
"Bayesian thinking: statistical modeling Python learning" Chinese PDF, from catalogs and bookmarks, text can be copied; English PDF, with the directory, text can be copied;
English version can compare two learning. Supporting source code;
Network disk download: http://106.13.73.98
