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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)
- Midterm grades
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 assignment
- Room 1: Cluster 507
- Room 2: Cluster 509
Others
- Tensorflow Dev Summit 2019 (link)
Google Sites
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