《机器学习》课程介绍
《机器学习》是计算机科学与技术专业的专业教育课。该课程的开设将使得计算机人才适应大数据时代的发展趋势，为学生从事与海量数据分析相关领域的工作奠定技术基础。机器学习是人工智能的一个重要分支，是研究学习的内在机制、建立能够利用历史数据提高自身效能的计算机程序的理论与方法的科学。随着各领域数据量的急剧膨胀，机器学习方法越来越显示出其强大的优势，逐渐成为计算机应用技术学科的基础及热点课程之一。机器学习方法的已经被成功应用到计算机视觉、自然语言处理、生物特征识别、搜索引擎、医学诊断、证券市场分析、语音识别和机器人控制等领域。
本课程的教学目的是：1）掌握机器学习领域的基本概念；2）掌握典型机器学习方法的应用技巧，能够运用机器学习方法来解决实际问题，如图像识别，文本分类，自然语言理解等；3）了解典型机器学习方法的基本原理；4）了解机器学习与人工智能技术的相关性。
本课程第6学期开设，计划32学时，先修课为：程序设计基础，数据结构，面向对象程序设计；后续课程为：可计算性与计算复杂性、生物信息学入门等。
The Introduction of Course --- Machine Learning
Machine learning is a major education course for the students of computer science and technology, which enables student to deal with the problems of massive data analysis and to be competent for big data times. As an important branch of artificial intelligence, machine learning focus on understanding and studying the mechanism of learning, and building the computer programs with the ability to improve themselves by using the historical data. With the drastic increasing of data in various fields, machine learning methods are showing their remarkable advantage, and becoming gradually one of the primary and hot courses of computer science and technology subject. In recent years, machine learning methods have been being applied successfully to various fields, including: image recognition, voice recognition, intelligent robot, credit card cheat detection, vehicle driving and prediction of non-linear time series, etc.
The goals of this course are as follows: 1) To master the primary concepts; 2) To master the skills in applications of machine learning technologies, being able to handle practical issues (such as: image recognition, text classification and natural language understanding) with machine learning methods; 3) To know about the basic theories under machine learning; 4) To know about the link between machine learning and artificial intelligence.
The course will be presented within 32 teaching-hours in the sixth term of the third academic year. Its pre-courses include basis of program design, data structure and object-oriented program design; and the post-courses include computability theory, and bioinformatics.
