MACHINE LEARNING

Topics Keras PyTorch Slides Problem Sets Solution

Installation colab installation

Python Basics of Python

Introduction pdf#00

Linear Algebra iColab#01 iColab#01 pdf#01 iPS#01 PS#01 Sol'n

Optimization iColab#02 iCoabl#02 pdf#02 iPS#02 PS#02 Sol'n

Regression iColab#03 iColab#03 pdf#03 iPS#03 PS#03 Sol'n

Classification iColab#04 iColab#04 pdf#04 iPS#04 PS#04 Sol'n

kNN, Decision Tree iColab#05 iColab#05 pdf#05 iPS#05 PS#05 Sol'n

Clustering: K-means iColab#06 iColab#06 pdf#06 iPS#06 PS#06 Sol'n

Dim. Reduction iColab#07 iColab#07 pdf#07 iPS#07 PS#07 Sol'n

Midterm Part I, Part II

Artificial Neural Networks (ANN) iColab#08 iColab#08 pdf#08 iPS#08 PS#08 Sol'n

Autoencoder iColab#09 iColab#09 pdf#09 iPS#09 PS#09 Sol'n

Convolutional Neural Networks (CNN) iColab#10 iColab#10 pdf#10 iPS#10 PS#10 Sol'n

Recurrent Neural Networks (RNN) iColab#11 iColab#11 pdf#11 iPS#11 PS#11 Sol'n

Physics-informed Neural Networks (PINN) iColab#12 iColab#12 pdf#12 iPS#12 PS#12 Sol'n

AI in ME: Fluid Mechanics iColab#13 iColab#13 pdf#13 iYouTube#13

AI in ME: Manufacturing iColab#14 iColab#14 pdf#14 iYouTube#14

AI in ME: Heat Transfer iColab#15 iColab#15 pdf#15 iYouTube#15

AI in ME: Solid Mechanics iColab#16 iColab#16 pdf#16 iYouTube#16

AI in ME: Dynamics iColab#17 iColab#17 pdf#17

Final Exam Part I, Part II

Topics Python Slides

Probability iNote#17 pdf#17

Gaussian Distribution iNote#18 pdf#18

Parameter Estimation iNote#19 pdf#19

Probabilistic Machine Learning iNote#20 pdf#20

Bayesian Machine Learning iNote#21 pdf#21

Topics Python

Independent Component Analysis (ICA) iNote#22

Singular Value Decomposition (SVD) iNote#23

Graph Theory iNote#24

Google PageRank iNote#25

Clustering: Spectral Partitioning iNote#26

Kalman Filter iNote#27

Gaussian Process iNote#28

Learning from Imbalanced Data iNote#29

Using Scikit-Learn iNote#30

Discrete Optimization iNote#31