機器學習已成功應用於許多現實世界的問題，目前產業界、科研領域都需要此方面人才。 本課程對象以大學部資工系(歡迎非資工系同學來選修)，對機器學習有興趣的學生為主。授課教師由本校資工系與數學系老師，擁有機器學習、理論、資料科學多年經驗的教師擔任，也邀請非常受學生歡迎的機器學習網路大神級人物台大李宏毅教授前來客座授課。
本課程目標是提供愛好機器學習同學學會深度學習技術，並能快速直接地解決實際和有趣的問題，式課方式深入淺出，介紹了機器學習基礎的model、核心概念和幾個常用的深度學習，包含如何訓練及優化類神經網路、深度神經網路(DNN)、卷積神經網路(CNN)、BP、RNN、SVM、KNN、非監督式學習、聊天機器人、EC廣告推撥系統…等， 還會透過實務專案、讓同學動手實作TensorFlow /Keras，期末專題同學組隊接受Kaggle競賽與實戰挑戰。Machine learning has been successfully applied to many real world problems, and talents in the industry and scientific research fields are currently needed. The subjects of this course are from the university department (not from the department of employment are welcome to choose from), and students who are interested in machine learning are mainly students. The teaching teacher is a teacher from the Department of Assets and Mathematics of the school. He has many years of experience in machine learning, theory and data science. Professor Li Hongyi, a master of machine learning online who is very popular among students, came to teach the class at a guest.
The purpose of this course is to provide in-depth learning techniques for Aihao Machine Learning and can quickly and directly solve practical and interesting problems. The course method is in-depth and introduces the basic model, core concepts and several commonly used in-depth learning of machine learning, including how to train and optimize neural networks, deep neural networks (DNN), volume neural networks (CNN), BP, RNN, SVM, KNN, non-supervised learning, chat robots, EC advertising push system, etc., It will also use practical projects and let students practice TensorFlow /Keras, and the final topic of the student team will accept Kaggle competition and actual battles.
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
In-depth learning Quick entry using tensorflow/Boyan Culture/ by Giancarlo Zaccone Translation of Fu Changwen
| 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 Action |
40 | |
| 課堂參與 (小考)課堂參與 (小考) Class Participation (Small Exam) |
10 |
