The Schedule

Lecture 2

2026/7/15

• 今天的實體課在土木系舊館4504教室上課，下午兩點開始上課。

• 上課資料網址與前次上課一樣。

• 直播視訊網址：https://meet.google.com/umm-esgw-xrs 

• 若是在線上觀看直播視訊，請於上線時在訊息欄寫「簽到：姓名或學號」，並於下線前在訊息欄寫「簽退：姓名或學號」

• 若需觀看之前上課的Youtube影音檔，請email我想要觀看哪些日期的影音檔，並提供成大的email address，我再各別分享給申請人。

• https://www.mathworks.com/help/deeplearning/gs/try-deep-learning-in-10-lines-of-matlab-code.html 

Lecture 3

2026/7/16

• 7/16 視訊網址：https://meet.google.com/bnn-jthf-ysg  

• 閱讀練習：[Textbook 1: Bishop]: all of Ch. 1. [Textbook 2: Singh] Ch. 1.1~1.3

• 作業 1 (deadline '1 Aug. 2026', 23:59:59): Please derive the equations for the linear regression analysis, and discuss how to derive the correlation coefficient R^2.

Lecture 4

2026/7/20

• 7/20 視訊網址：https://meet.google.com/yzv-ykjq-vek 

• 閱讀練習：[Textbook 1: Bishop]: all of Ch. 2. [Textbook 2: Singh] Ch. 3.1~3.8

• Norm: https://en.wikipedia.org/wiki/Norm_(mathematics) 

• Newton-Raphson iteration method: https://en.wikipedia.org/wiki/Newton%27s_method 

• Gradient descent: https://en.wikipedia.org/wiki/Gradient_descent 

• Conjugate gradient descent: https://en.wikipedia.org/wiki/Conjugate_gradient_method 

• Stochastic gradient descent: https://en.wikipedia.org/wiki/Stochastic_gradient_descent 

• Supervised learning: https://en.wikipedia.org/wiki/Supervised_learning 

• Unsupervised learning: https://en.wikipedia.org/wiki/Unsupervised_learning 

• Semi-supervised learning: https://en.wikipedia.org/wiki/Weak_supervision 

• Self-supervised learning: https://en.wikipedia.org/wiki/Self-supervised_learning 

• Reinforcement learning: https://en.wikipedia.org/wiki/Reinforcement_learning 

• Naive Bayes classification: https://en.wikipedia.org/wiki/Naive_Bayes_classifier 

• https://www.wolfram.com/language/introduction-machine-learning/ 

Lecture 5

2026/7/21

• 7/21 視訊網址：https://meet.google.com/nbn-rhqy-xsw

• https://en.wikipedia.org/wiki/Lagrange_multiplier 

• https://en.wikipedia.org/wiki/Bayesian_linear_regression  

• https://en.wikipedia.org/wiki/Normal_distribution  

• https://en.wikipedia.org/wiki/Laplace_distribution 

• https://en.wikipedia.org/wiki/Ridge_regression 

• https://en.wikipedia.org/wiki/Maximum_likelihood_estimation 

• https://en.wikipedia.org/wiki/Learning_rate 

• https://en.wikipedia.org/wiki/Bias–variance_tradeoff 

• https://en.wikipedia.org/wiki/Elastic_net_regularization 

Lecture 6

2026/7/22

• 7/22 視訊網址：https://meet.google.com/qqb-jmnj-ejf

• https://www.wolfram.com/language/introduction-machine-learning/bayesian-inference/# 

Lecture 7

2026/7/29

• https://meet.google.com/vjg-ffqx-rym 

• https://www.mathworks.com/help/releases/R2026a/deeplearning/ug/sequence-to-sequence-classification-using-deep-learning.html 

• https://www.mathworks.com/help/releases/R2026a/deeplearning/ug/sequence-to-one-regression-using-deep-learning.html 

• https://www.mathworks.com/help/releases/R2026a/deeplearning/ug/train-residual-network-for-image-classification.html 

• https://www.mathworks.com/help/releases/R2026a/deeplearning/ug/classify-sequence-data-using-lstm-networks.html 

• https://www.mathworks.com/help/releases/R2026a/deeplearning/ug/train-network-on-image-and-feature-data.html 

• https://www.mathworks.com/help/releases/R2026a/deeplearning/ug/create-simple-deep-learning-network-for-classification.html 

• https://www.mathworks.com/help/releases/R2026a/deeplearning/ug/generate-images-using-guided-diffusion.html 

• https://www.mathworks.com/help/releases/R2026a/deeplearning/ug/train-generative-adversarial-network.html 

• https://www.mathworks.com/help/releases/R2026a/deeplearning/ug/solve-pde-using-fourier-neural-operator.html 

• https://www.mathworks.com/help/releases/R2026a/deeplearning/ug/solve-partial-differential-equations-with-lbfgs-method-and-deep-learning.html 

• https://www.mathworks.com/help/releases/R2026a/deeplearning/ug/long-short-term-memory-networks.html 

• https://www.mathworks.com/help/releases/R2026a/deeplearning/ug/train-a-convolutional-neural-network-for-regression.html 

• https://www.mathworks.com/help/releases/R2026a/deeplearning/ug/create-simple-deep-learning-network-for-classification.html 

• https://www.mathworks.com/help/releases/R2026a/reinforcement-learning/ug/train-reinforcement-learning-agent-in-mdp-environment.html 

• https://www.mathworks.com/help/releases/R2026a/reinforcement-learning/ug/control-water-level-using-ddpg-agent.html 

Lecture 8

2026/7/30

• https://meet.google.com/szj-pmmt-tkh 

Lecture 9

2026/7/31

• https://meet.google.com/bqy-ycaf-fac 

Lecture 10

2026/8/3

Lecture 11

2026/8/5

Lecture 12

2026/8/7

Lecture 13

2026/8/10

Lecture 14

2026/8/12

Lecture 15

2026/8/14

Lecture 16

2026/8/17

Lecture 17

2026/8/19

Lecture 18

2026/8/21