機器學習商業應用
Machine Learning for Business
| 節 | 週四 |
|---|---|
6 14:20–15:10 | 機器學習商業應用 M301（光復） 3 節連堂 |
7 15:30–16:20 | |
8 16:30–17:20 |
* 根據陽明交大上課時間表所列
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.
商業智慧分析 Intermediate knowledge of Python Programming and Statistics
無備註
TAs
1. Homework and Assignment: 13 Homeworks & 1 Final Project (Late Submission Will Not be Accepted) 2. Exams and Quizzes: Midterm Exam 3. Evaluation and Grading Policy: 13 Homework 40%, Midterm Exam 30%, Final Project 30%
教師未提供此項資料
| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction for Machine Learning |
| 第 2 週 | Supervised Learning & Linear Models for Regression / HW1 |
| 第 3 週 | Supervised Learning & Linear Models for Classification / HW2 |
| 第 4 週 | Model Evaluations & Metrics / HW3 |
| 第 5 週 | Model Training / HW4 |
| 第 6 週 | Supervised Learning & SVM / HW5 |
| 第 7 週 | Trees, Forests & Ensemble Learning / HW6 |
| 第 10 週 | Midterm Exam |
| 第 11 週 | Model Parameter Tuning / HW8 |
| 第 12 週 | Unsupervised Learning & Dimensionality Reduction / HW9 |
| 第 13 週 | Unsupervised Learning & Clustering / HW10 |
| 第 14 週 | Working with Imbalanced Data / HW11 |
| 第 15 週 | Working with Text Data I |
| 第 16 週 | Working with Text Data II / HW12 |
| 第 17 週 | Neural Networks / HW13 |
| 第 18 週 | Final Project Submission |
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
- 地點
- M301
- 時間
- 4:30 - 5:30 pm on Thursday
- 聯絡方式
- E3 Email