Project data suggetions

• UCI Machine Learning Repository

• Kaggle

• 공공데이터포털

• data.gov

• Submit Proposal

"dongykang@gmail.com"

*The form of E-mail head,title must be like this.

(if you do not keep that form, TA will not read.)

[cse4048][Student ID][name] title

Homeworks

• HW1 (due April 27 by 12:00pm @ Cluster Bd. #620. No late submission will be accepted)

  • dnn_mnist.py

  • Creating DNN with Tensorflow [Video Lecture 07]

  • Task 2: you can assume that the keys for hidden layers in the dictionary start with the character 'h'

• HW2 (due June 1, by 12:00pm @ Cluster Bd. #620. No late submission will be accepted)

  • cnn_mnist.py

  • Creating CNN with TF [Video Lecture 08]

• HW3 (due June 15, by 12:00pm @ Cluster Bd. #620. No late submission will be accepted)

  • autocomplete.py

  • Creating RNN with TF [Video Lecture 09]

Lecture Videos

• 1. Basic Math (link)

• 2. Probability (link)

• 3. MLE (link)

• 4. Training problem (link)

• 5. SGD (link)

• 6. Back-propagation (link)

• 7. DNN with TF (link)

• 8. CNN with TF (link)

• 9. RNN with TF (link)

• 10. Activation function 1 (link)

• 11. Activation function 2 (link)

• 12. Pre-processing (link)

• 13. Dropout & batch-normalization (link)

Lecture Notes

• Lecture 01. Introduction [pdf]

• Lecture 02. Machine learning basics [pdf]

• Lecture 03. Multi-Layer Perceptron [pdf]

• Lecture 04. Introduction to Tensorflow [pdf]

• Lecture 05. Tensorflow: linear regression, logistic regression [code]

• Lecture 06. Convolutional neural network 1 [pdf]

• Lecture 07. Convolutional neural network 2 [pdf]

• No lecture on April 27

  • Make-up lecture on May 2, 1:30~3:00 @ usual classroom (Cluster Bd. PBL Purple)

• Lecture 08-09. Recurrent neural network [pdf]

• Lecture 10. Advanced Topics: GPU, Initialization, Hyperparameter Tuning [pdf]

• Lecture 11. Project discussion

• Lecture 12. Project discussion

• Lecture 13. Project check

• Lecture 14 (June 14) 16:30 ~ 17:30 @ Eng Bd #1, R.305

• Advanced Topics: Activation functions, Dropout [pdf]