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Time: Tue 10:30-12:00pm
Location: Cluster Bd. (학연산클러스터) Buzzing Blue Room (5th floor)
Textbook: Deep Learning, Goodfellow, Bengio, Courville, MIT Press, 2016
Grading:
Homeworks, Midterm, Final Exam = 30%, 30%, 30%
Attendance: 10% (offline)
Homeworks
HW1 (due April 12, 1pm @ AILAB HW Box) .
HW2 (due May 10, 1pm @ AILAB HW Box)
HW3 (due May 24, 1pm @ AILAB HW Box)
Lecture Notes
Lecture 1. Introduction (pdf)
Lecture 2. Intro. to Machine Learning & Deep Learning (pdf)
Lecture 3. Multi-layer perceptron (pdf)
Lecture 4. Intro to Tensorflow (pdf, code)
V4. DNN with TF (video)
Lecture 5. Convolutional Neural Networks I (pdf)
Lecture 6. Convolutional Neural Networks II (pdf)
Lecture 7. Summary (pdf)
Midterm (April 23, in-class 10:30~12:30)
Lecture 8. Midterm review, Recurrent Neural Network I (pdf)
V8. CNN with TF (video)
HW2 is out!
Lecture 9. Recurrent Neural Network II
V9. RNN with TF (video)
Lecture 10. TF 2.0 (dnn_tf1, dnn_tf2 / cnn_tf1, cnn_tf2 / cnn_tf2_logging, tf2_tensorboard)
Lecture 11. Generative Adversarial Network (pdf)
Lecture 12. Word2Vec (pdf)
Lecture 13. Summary (pdf)
Final exam (June 11, in class)
Content: Lectures 8~13 (including video lectures)
Room 1: Cluster 507
Room 2: Cluster 509
Others
Tensorflow Dev Summit 2019 (link)
Google Sites
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