ARTIFICIAL INTELLIGENCE

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Machine Learning, 2020 [YouTube]

Dates Topics with Python Slides Homework Solution
Installation python installation
docker installation (optional)
Python Basics of Python
03/17/20 Introduction iNote#00 pdf#00
03/19/20
03/24/20
03/26/20
Linear Algebra iNote#01 pdf#01 HW#01 HW#01 Solution
03/31/20
04/02/20
Optimization iNote#02 pdf#02 HW#02 HW#02 Solution
04/07/20
04/09/20
04/14/20
Regression: Basics
Regression: Overfitting and Regularization
Regression: Examples
iNote#03_1
iNote#03_2
iNote#03_3
pdf#03 HW#03 HW#03 Solution
04/16/20
04/21/20
04/23/20
04/28/20
Classification: Perceptron
Classification: SVM
Classification: Logistic Regression
iNote#04
iNote#05
iNote#06
pdf#04
pdf#05
pdf#06
HW#04
HW#05
HW#06
HW#04 Solution
HW#05 Solution
HW#06 Solution
05/07/20 Midterm
05/12/20
05/14/20
K-NN
Decision Tree
iNote#07
iNote#08
pdf#07
pdf#08
HW#07 HW#07 Solution
05/19/20 Clustering: K-means iNote#09 pdf#09 HW#08
05/21/20 Statistics iNote#10 pdf#10
05/26/20
05/28/20
Dim. Reduction: PCA
Dim. Reduction: FDA
iNote#11
iNote#12
pdf#11
pdf#12
Artificial Neural Networks iNote#13_1
iNote#13_2
iNote#13_3
pdf#13
Dim. Reduction: Autoencoder iNote#14 pdf#14
Final Exam

 

Probabilistic Machine Learning [YouTube]

Dates Topics with Python Slides Homework Solution
Probability iNote#16 pdf#16
Gaussian Distribution iNote#17 pdf#17
Parameter Estimation iNote#18 pdf#18
Probabilistic Machine Learning iNote#19 pdf#19
Bayesian Machine Learning iNote#20 pdf#20

 

Deep Learning, 2020 [YouTube]

Dates Topics with Python Slides Homework Solution
Installation python installation
docker installation (optional)
Python Basics of Python
03/17/20 Introduction pdf#00
03/19/20 Optimization iNote#01 pdf#01 HW#01 HW#01 Solution
03/24/20
03/26/20
03/31/20
04/02/20
Machine Learning

Machine Learning with TensorFlow

iNote#02_1

iNote#02_2

pdf#02 HW#02 HW#02 Solution
04/07/20
04/09/20
SGD
Overfitting
iNote#03
iNote#04
pdf#03
pdf#04
HW#03 HW#03 Solution
04/14/20
04/16/20
04/21/20
04/23/20
ANN: From Perceptron to MLP (ANN)
ANN: Training
ANN: MNIST
ANN: Advanced
iNote#05_1
iNote#05_2
iNote#05_3
iNote#05_4
pdf#05 HW#04
HW#05
HW#04 Solution
HW#05 Solution
04/28/20 Autoencoder (AE) iNote#06 pdf#06 HW#06 HW#06 Solution
05/07/20 Midterm
Colab Installation iNote#
05/12/20
05/14/20
05/19/20
Convolutional Neural Networks (CNN)
Class Activation Maps (CAM)
iNote#07
iNote#08
iNote#09
pdf#07
pdf#08
pdf#09
HW#07 HW#07 Solution
05/21/20 Modern CNNs
Transfer Learning
iNote#10 pdf#10
05/26/20
05/28/20
Convolutional Autoencoders (CAE)
Fully Convolutional Networks (FCN)
iNote#11
iNote#12
pdf#11
pdf#12
HW#08
Generative Adversarial Networks (GAN) iNote#13 pdf#13
Style Transfer iNote#14 pdf#14
Time Series Data
Recurrent Neural Networks (RNN)
iNote#15
iNote#16
pdf#15
pdf#16
Final Exam

 

Deep Reinforcement Learning

Dates Topics with Python Slides Homework Solution
Fixed-Point Iteration iNote#17
Dynamic Programming iNote#18
MDP: Markov Chain
MDP: Markov Reward Process (MRP)
MDP: Markov Decision Process (MDP)
iNote#19_1
iNote#19_2
iNote#19_3
Reinforcement Learning iNote#20
Deep Reinforcement Learning iNote#21