人工智慧：機器學習與理論基礎 (Artificial Intelligence - Learning & Theory)(으)로 돌아가기
국립 타이완 대학의 人工智慧：機器學習與理論基礎 (Artificial Intelligence - Learning & Theory) 학습자 리뷰 및 피드백
26개의 평가
강좌 소개
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
최상위 리뷰
필터링 기준:
人工智慧：機器學習與理論基礎 (Artificial Intelligence - Learning & Theory)의 3개 리뷰 중 1~3
교육 기관: Jie-Han C
•Aug 07, 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.
교육 기관: Pin-Yu C
•Jul 06, 2020
NICE!!!!
교육 기관: Alan
•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.
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