校際選修

115-1 選課時程

進行中

  • 初選第一階段 6/15/2026
  • 初選第二階段 6/22/2026
  • 校際選修 8/24/2026
  • 初選第三階段 8/31/2026
  • 開學後加退選 9/7/2026
  • 逾期加退選 9/21/2026
選課資源

深度學習

Deep Learning

學期
107-2
學分
3 學分
當期課號
5076
永久課號
ECM9042
開課單位
電信工程研究所
授課教師
簡仁宗
校區
光復
類別
選修
上課時間表
週五
5
13:20–14:10
深度學習
ED219
3 節連堂
6
14:20–15:10
7
15:30–16:20

* 根據陽明交大上課時間表所列

概述

Deep learning is a branch of machine learning based on a set of algorithms that attempt to model high level abstractions in data by using a deep graph with multiple processing layers, composed of multiple linear and nonlinear transformations. Various deep learning architectures such as deep neural networks, convolutional deep neural networks, deep belief networks and recurrent neural networks have been applied to fields like computer vision, automatic speech recognition, natural language processing, audio recognition and bioinformatics where they have been shown to produce state-of-the-art results on various tasks.

先修科目

Calculus, Linear Algebra, Probability & Statistics

教學方式

Teaching notes or slides will be provided. Teacher assistants (陳幽秀、蔡知融、黃煜閔、邱奕中、許伯阡) will be available at PM19:30-20:30 in ED 912 in week days.

評分方式

Temporary Policy: Final Exam (40%), Homework (40%), Final Project (20%), Class Attendance (+10%)

課程大綱
週次計畫
週次主題
第 1 週Introduction to Deep Learning
第 2 週Deep Feedforward Networks
第 3 週Regularization for Deep Learning
第 4 週Tutorial for Pytorch & GPU Server
第 5 週Optimization for Deep Models
第 6 週Optimization for Deep Models
第 7 週Convolutional Neural Networks
第 8 週Recurrent Neural Networks
第 9 週Memory Networks
第 10 週Attention Mechanism
第 11 週Auto-Encoders & Approximate Inference
第 12 週Variational Auto-Encoders
第 13 週Introduction to Final Project/Generative Adversarial Networks
第 14 週Generative Adversarial Networks
第 15 週Deep Domain Adaptation
第 16 週Reinforcement Learning
第 17 週Final Exam
第 18 週Project Presentation
教科書

1. I. Goodfellow and Y. Bengio and A. Courville, Deep Learning, The MIT Press, 2016 (http://www.deeplearningbook.org) 2. J.-T. Chien, Source Separation and Machine Learning, Academic Press, October 2018. 3. S. Watanabe and J.-T. Chien, Bayesian Speech and Language Processing, Cambridge University Press, 2015.

Office Hours
地點
ED 912
時間
PM17:00-18:00 on Thursday
聯絡方式
jtchien@nctu.edu.tw