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。 這課程為基礎簡介， 對象大學部學生為主。我們以深入淺出，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，也包含數學理論間意基礎與實作，model包括線性模型、regression、非線性模型、深度前饋網絡、深度學習、CNN的演算法，也帶同學研讀deep mind’s alphago論文，為同學日後研究打下基礎。課程並說明許多實際實務應用，包含g.手寫字辨識、語音辦認、影像、EC廣告推撥。另外， 也教導pythont程式語言與TensorFlow，以此實作機器學的範例與練習。Machine learning has been successfully applied to many real world problems, and talents in the industry and scientific research fields are currently needed. This course is a basic introduction, mainly targeting university department students. We have introduced the model, core concepts and several commonly used deep learning based on machine learning, and also includes mathematical theory conscious basis and implementation. Model includes linear models, regression, non-line models, deep precursor networks, deep learning, and CNN algorithms. We also study deep mind’s alphago papers to lay the foundation for future research of classmates. The course also explains many practical applications, including g. manual word identification, voice recognition, video, and EC advertising promotion. In addition, we also teach pythont programming language and TensorFlow to use this to implement examples and practices of machine learning.
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/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 |
25 | |
| 作業 作業 Action |
40 | |
| 課堂參與 (小考)課堂參與 (小考) Class Participation (Small Exam) |
15 |
