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Learner Reviews & Feedback for 人工智慧:機器學習與理論基礎 (Artificial Intelligence - Learning & Theory) by National Taiwan University

4.6
stars
61 ratings

About the Course

本課程第二部分著重在和人工智慧密不可分的機器學習。課程內容包含了機器學習基礎理論(包含 1990 年代發展的VC理論)、分類器(包含決策樹及支援向量機)、神經網路(包含深度學習)及增強式學習(包含深度增強式學習。 此部份技術包含最早追溯至 1950 年代直到最近 2016 年附近的最新發展。此課程從基礎理論開始,簡介了各機器學習主流技法以及從淺層學習架構演變到最近深度架構的轉換。 本課程之核心目標為: (一)使同學對人工智慧相關的機器學習技術有基礎概念 (二)同學能夠理解機器學習基礎理論、分類器、神經網路、增強式學習 (三)同學能將相關技術應用到自己的問題上 修課前,基礎背景知識: 需要的先備知識:計算機概論 建議的先備知識:資料結構與演算法...

Top reviews

KJ

Jan 4, 2022

Professor Ding's teaching is conscientious and the lectures are clearly explained

EC

Aug 7, 2019

整體上, 是值得推薦的入門課程, 把machine learning的基本課程與熱門的topics提出來講. 習題的內容算簡單, 大部份在檢驗觀念.

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1 - 10 of 10 Reviews for 人工智慧:機器學習與理論基礎 (Artificial Intelligence - Learning & Theory)

By Chan C

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Apr 26, 2020

Lecturer explains concepts very clearly and explanations are easy to understand. I am so interested in AI and trying to find a way to get into the field. The course is so good for someone like me to get started. I give 4 stars because there are some obviously wrong answers for some questions and some learners also point out by using forum. However, lecturer or TA doesn't reply. Beside, I also try to contact with lecturer via NTU email but still no any response. I think this is the most worst point at this lecture. Thanks.

By kuo j

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Jan 4, 2022

Professor Ding's teaching is conscientious and the lectures are clearly explained

By 許又升

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Mar 2, 2024

当初没有注意到这是给有一点基础的人上的课,因為自己完全没有基础但想试试看学习人工智慧的基础理论,不过老师讲得非常好,做笔记重复看还是可以听得懂大部分的内容

By Eli C

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Aug 7, 2019

整體上, 是值得推薦的入門課程, 把machine learning的基本課程與熱門的topics提出來講. 習題的內容算簡單, 大部份在檢驗觀念.

By Indi C

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Oct 1, 2024

Good introduction on ML and Deep Learning

By 楓糖FT

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Mar 13, 2022

非常有帮助!很适合先修

By 陳品妤

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Jul 6, 2020

NICE!!!!

By 陳詩誼

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Oct 1, 2022

good

By 劉亦倩

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Oct 11, 2021

老师讲解清楚,习题测验也算简单,主要是检验观念

By Wang J

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Jan 26, 2025

这个老师讲得不好; 第一英语与中文混杂早晨口齿不清、第二对概念的解释过于直接从英语字面解释,没有用自己理解的话重新叙述、第三举例不够清楚