Machine Learning Course Information Rui Xia School of Computer - PowerPoint PPT Presentation

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Machine Learning Course Information Rui Xia School of Computer Science & Engineering Nanjing University of Science & Technology rxia@njust.edu.cn http://www.nustm.cn/member/rxia 2018/9/10 Machine Learning, by Rui Xia @ NJUST 1

Machine Learning Course Information Rui Xia School of Computer Science & Engineering Nanjing University of Science & Technology rxia@njust.edu.cn http://www.nustm.cn/member/rxia 2018/9/10 Machine Learning, by Rui Xia @ NJUST 1
Contact • Lecturer (Rui Xia) – Email: rxia@njust.edu.cn – Homepage: http://www.nustm.cn/member/rxia – Address: Room 3030, School of CS • Teaching Assistant (Kaizhou Xuan) – Phone: 18751897908 • QQ Group: 815382854 • Course Webpage http://www.nustm.cn/member/rxia/ml/ 2018/9/10 Machine Learning, by Rui Xia @ NJUST 2
Syllabus • An Introduction to Machine Learning • Linear Regression • Logistic Regression and Softmax Regression • Perceptron Algorithm • Simple Neural Network and Back Propagation • Generative Model vs. Discriminative Model • Naïve Bayes Model • K-means Clustering • Application: Text Classification as an Example 2018/9/10 Machine Learning, by Rui Xia @ NJUST 3
Course Assessment • In-class behavior (10%) – Questions/Answers – Some assignments to be finished in class • Projects and oral presentations (40%) – Content • 1) The review of the machine learning model you chose; • 2) The implementation of the model; • 3) The report of the experimental results. – Note • 4-5 students/one group; • 15 minutes slides/presentation; • The contribution of each group member should be specified. • Final examination (50%) – Open-book examination in English 2018/9/10 Machine Learning, by Rui Xia @ NJUST 4
References • English Materials – Prof. Andrew Ng's machine learning course at coursera.org; ( ★ , number of stars means the level of reading difficulty) – Prof. Andrew Ng's machine learning class at Stanford University [materials] [video]; ( ★★★ ) – Christopher Bishop. Pattern Recognition and Machine Learning, 2007. ( ★★★★★ ) – T. Hastie, R. Tibshirani, and J. Friedman. The Elements of Statistical Learning, 2001. ( ★★★★★ ) • Chinese Materials – 周志华 . 机器学习 , 清华大学出版社 , 2016. ( ★★ ) – 李航 . 统计学习方法 , 清华大学出版社 , 2012. ( ★★★ ) 2018/9/10 Machine Learning, by Rui Xia @ NJUST 5
Any Questions? 2018/9/10 Machine Learning, by Rui Xia @ NJUST 6

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