課程名稱 |
物聯網下商管統計分析 Quantitative Business Science |
開課學期 |
108-2 |
授課對象 |
管理學院 工商管理學系 |
授課教師 |
楊曙榮 |
課號 |
MBA5078 |
課程識別碼 |
741EU7220 |
班次 |
|
學分 |
3.0 |
全/半年 |
半年 |
必/選修 |
選修 |
上課時間 |
星期四7,8,9(14:20~17:20) |
上課地點 |
管二201 |
備註 |
本課程以英語授課。 限學士班三年級以上 總人數上限:50人 |
Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1082MBA5078_ |
課程簡介影片 |
|
核心能力關聯 |
本課程尚未建立核心能力關連 |
課程大綱
|
為確保您我的權利,請尊重智慧財產權及不得非法影印
|
課程概述 |
In recent years, business analytics skills have become essential for those pursuing careers in consulting and data-driven organizations. This course develops models and algorithms for central problems in predictive and prescriptive analytics from an optimization perspective and discusses their impact. Topics include regression, classification, images, sequences, deep learning, generative models, and their relationships with mathematical programming and operations research. We explain analytics from the first principle of constructing different machine learning models and understanding the role of hyperparameters in these models while building them up from scratch. |
課程目標 |
We offer a concise coverage of the core knowledge needed to build new analytical models for anlayzing data and developing data-driven products. The ultimate learning outcome is to create data-driven applications on operations, logistics, supply chains, marketing, and smart business. |
課程要求 |
The course is aimed at the numerate students who have the knowledge of calculus, computer programming, linear algebra, probability, and statistics; please see the instructor if you are unsure whether your background is suitable for the course. We use the Python programming language with the Keras library in the TensorFlow environment. |
預期每週課後學習時數 |
|
Office Hours |
|
指定閱讀 |
Goodfellow, I., Y. Bengio, A. Courville. 2016. Deep Learning. The MIT Press.
Chollet, F. 2017. Deep Learning with Python. Manning Publications. |
參考書目 |
Deisenroth, M. A., A. Faisal, C. S. Ong. 2020. Mathematics for Machine Learning. Cambridge
University Press.
Downey, A. 2015. Think Python 2e.
Winston, W. L. 2004. Operations Research: Applications and Algorithms. Thomson
Learning, Inc. |
評量方式 (僅供參考) |
|
|