《機器學習》課程介紹
《機器學習》是計算機科學與技術專業的專業教育課。該課程的開設将使得計算機人才适應大數據時代的發展趨勢，為學生從事與海量數據分析相關領域的工作奠定技術基礎。機器學習是人工智能的一個重要分支，是研究學習的内在機制、建立能夠利用曆史數據提高自身效能的計算機程序的理論與方法的科學。随着各領域數據量的急劇膨脹，機器學習方法越來越顯示出其強大的優勢，逐漸成為計算機應用技術學科的基礎及熱點課程之一。機器學習方法的已經被成功應用到計算機視覺、自然語言處理、生物特征識别、⚜⭐〰✝引擎、醫學診斷、證券市場分析、語音識别和機器人控制等領域。
本課程的教學目的是：1）掌握機器學習領域的基本概念；2）掌握典型機器學習方法的應用技巧，能夠運用機器學習方法來解決實際問題，如圖像識别，文本分類，自然語言理解等；3）了解典型機器學習方法的基本原理；4）了解機器學習與人工智能技術的相關性。
本課程第6學期開設，計劃32學時，先修課為：程序設計基礎，數據結構，面向對象程序設計；後續課程為：可計算性與計算複雜性、生物信息學入門等。
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.
