本課程將介紹機器學習以及類神經網路的基本概念，並介紹目前廣泛使用的 Google TensorFlow 軟體庫，讓學生學會如何使用 Python 及 TensorFlow 開發各種機器學習應用，例如: 模式辨識、手寫文字辨識、圖像辨識、sentiment analysis、language modeling…等。同時也包含工學院各領域的機器學習應用，例如: 生產品質檢測、光譜分析、空汙預測、自動化載具控制...等。此外，本課程將搭配相關工具軟體的實際演練，讓學生未來可易於將所學套用在研究與工作上。This course will introduce the basic concepts of machine learning and neural networks, and introduce the currently widely used Google TensorFlow software library, allowing students to use Python and TensorFlow to develop various machine learning applications, such as: mode identification, handwriting text identification, image identification, sentiment analysis, language modeling..., etc. It also includes machine learning applications in various fields of the Institute of Technology, such as: product quality detection, optical spectrum analysis, space prediction, automatic load control, etc. In addition, this course will be accompanied by actual practice of related tool software, so that students can easily apply what they have learned to research and work in the future.
Sebastian Raschka, Vahid Mirjalili, Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow, 2nd Edition., Packt Publishing Limited, September 20, 2017.
Sebastian Raschka, Vahid Mirjalili, Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow, 2nd Edition., Packt Publishing Limited, September 20, 2017.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 課堂參與課堂參與 Class Participation |
20 | |
| 作業作業 Action |
80 |
