8/24 – 9/18

115-1 選課時程

進行中

  • 初選第一階段 6/15 – 6/18
  • 初選第二階段 6/22 – 6/25
  • 校際選修 進行中 8/24 – 9/18
  • 初選第三階段 8/31 – 9/3
  • 開學後加退選 9/7 – 9/21
  • 逾期加退選 9/21 – 9/24
選課資源

加入行事曆

選擇訂閱 Google Calendar,或下載通用的 ICS 檔案。

使用 Google Calendar 時,Google 會收到這份課表的公開連結。

機器學習商業應用

Machine Learning for Business

學期
109-2
學分
0 學分
當期課號
5502
永久課號
IMS5371
開課單位
管理科學系
授課教師
向倩儀
校區
光復
類別
選修
上課時間表
週二
5
13:20–14:10
機器學習商業應用
M105(光復)
3 節連堂
6
14:20–15:10
7
15:30–16:20

* 根據陽明交大上課時間表所列

概述

This class provides students with a hands-on approach to the machine learning landscape and focuses on machine learning algorithms' applications on real-world datasets. The students in this class will understand and implement the most popular learning algorithms and apply Scikit-Learn to build a machine-learning project end-to-end. This course will also emphasize the applications of machine learning models in business analytics.

先修科目

Intermediate knowledge of Python programming and Statistics

備註

無備註

教學方式

1. Pedagogy and other supplementary information: TAs 2. Late Submission Will Not be Accepted

評分方式

1. Homework and Assignment: 10 Homeworks & 1 Final Project 2. Exams and Quizzes: Midterm Exam 3. Evaluation and Grading Policy: 10 Homework 60%, Midterm Exam 20%, Final Project 20%

課程大綱

教師未提供此項資料

週次計畫
週次主題
第 1 週Introduction
第 2 週Supervised Learning & Linear Models for Regression / HW1
第 3 週Supervised Learning & Linear Models for Classification / HW2
第 4 週Trees, Forests & Ensemble Learning / HW3
第 5 週Model Evaluations & Metrics
第 6 週Model Interpretations / HW4
第 7 週No Class
第 8 週Midterm Exam
第 9 週Feature Selection
第 10 週Model Parameter Tuning / HW5
第 11 週Unsupervised Learning & Dimensionality Reduction / HW6
第 12 週Clustering & Gaussian Mixtures / HW7
第 13 週Working with Imbalanced Data / HW8
第 14 週Working with Time Series Data / HW9
第 15 週Neural Networks / HW10
第 16 週Recommender Systems
第 17 週Final Project
教科書

1. The documentation for the latest version of Scikit-learn https://scikit-learn.org/stable/user_guide.html 2. Title: Introduction to Machine Learning with Python: A Guide for Data Scientists, 1st Edition (not required) Author(s): Andreas C. Müller, Sarah Guido Release date: October 2016 Publisher(s): O'Reilly Media, Inc. ISBN: 9781449369415 3. Title: Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition (not required) Author(s): Aurélien Géron Release date: September 2019 Publisher(s): O'Reilly Media, Inc. ISBN: 9781492032649

Office Hours
地點
The Classroom
時間
TA Hour 12:50 - 1:20 pm Office Hour 4:30 - 5:30 pm Tuesdays
聯絡方式
E3