Analyzation and application of PyMC3

Abstract

 This article studies and analyzes the data of “student study hour”. The purpose of this article is to analyze the relationship between students' learning hours and the score. Data analysis involves machine learning and algorithms. Therefore, these two parts and their related knowledge need to be learned and mastered. In the following part, the article will first introduce the utilization methods, which are machine learning, Bayesian method and PyMC3. Then, the article introduces the details of the analysis steps for the “student study hour” data. The conclusion will be presented at the end of the article, which concludes the linear relation of the data, and the pros and cons of PyMC3.