目前產業界、科研領域都需要AI人才。本課目標提供愛好AI同學學會機器學習技術，能夠快速、系統化掌握人工智慧技術的最新趨勢，並徹底瞭解人工智慧如何運作。
課程會先總攬機器學習的理論，包括分類、定義問題與方法，接著進入機器學習的核心神經網路的重要概念，搭配手把手實例與自行練習，不僅對於理論深度掌握，並且實作類神經網路。
課程中將介紹企業實際案例，並邀請業界進行實務及專題分享。期末成果舉行發表會，邀請企業執行長、技術主管擔任評審，做為同學就業提前部屬。
對象:大學部資工系(非資工系同學亦可)。需要有程式基礎，python 更佳。歡迎想要一次把AI、機器學習學好、學滿的同學選修。
教師:蔡清欉；合作教師賴泳瑄(黑瘋科技) 、陳仕偉。三位都具備產業實務，課程也邀請非常受學生歡迎名師前來客座授課。
At present, AI talents are needed in both industry and scientific research fields. The goal of this course is to provide AI-loving students with the ability to learn machine learning technology, quickly and systematically grasp the latest trends in artificial intelligence technology, and thoroughly understand how artificial intelligence operates.
The course will first provide an overview of the theory of machine learning, including classification, definition of problems and methods, and then go into the important concepts of neural networks, the core of machine learning, with hands-on examples and self-exercises. Not only will you have a deep grasp of the theory, but you will also be able to implement neural networks. .
In the course, actual corporate cases will be introduced, and the industry will be invited to share practical and special topics. A press conference will be held for the final results, and company CEOs and technical directors will be invited to serve as reviewers and serve as early subordinates for students' employment.
Target audience: University Department of Finance and Engineering (students from non-Scholarship and Engineering Departments are also welcome). A programming foundation is required, python is preferred. Students who want to learn AI and machine learning well in one go are welcome to take this course.
Teacher: Cai Qingzhen; co-teachers Lai Yongxuan (Heifeng Technology) and Chen Shiwei. All three have industrial experience, and the course also invites famous teachers who are very popular among students to give guest lectures.
Pattern Recognition and Machine learning, bishop springer
Deep learning, Ian Goodfellow, Yoshua Bengio and Aaron Courville, 2016
深度學習快速入門 使用tensorflow/ 博碩文化 / Giancarlo Zaccone 著 傅運文翻譯
Pattern Recognition and Machine learning, bishop springer
Deep learning, Ian Goodfellow, Yoshua Bengio and Aaron Courville, 2016
Quick Start with Deep Learning Using TensorFlow/ Boshuo Culture / Written by Giancarlo Zaccone Translated by Fu Yunwen
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 期中考期中考 midterm exam |
20 | |
| 期末考期末考 final exam |
30 | |
| 作業作業 Homework |
40 | |
| 課堂參與 (小考)課堂參與 (小考) Class Participation (Quiz) |
10 |
