Instructor | Chaiwoot Boonyasiriwat |
Class Hours | Friday, 9.00AM - 12.00PM |
Classroom | Computer lab (6th floor) |
Grading | assignment 60, project 40 |
Slides |
Date | Topics | Assignments |
---|---|---|
Jan 12, 2024 | Python programming | |
Jan 19, 2024 | Introduction to deep learning, data representation, perception, linear regression, gradient descent method | |
Jan 26, 2024 | Least-squares method, stochastic gradient descent, multiple linear regression, polynomial regression
AqSolDB.csv |
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Feb 2, 2024 | Multiple linear regression ( data1.csv, data1.meta, data2.csv, data2.meta, data3.csv, data3.meta, data4.csv, data4.meta) | |
Feb 9, 2024 | Multilayer perceptron (MLP), training MLP | |
Feb 15, 2024 | Image classification (continued) Dataset: seven_classes.zip |
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Feb 23, 2024 | Transfer learning | |
Mar 6, 2024 | Image segmentation Dataset: oxford_pets.zip |
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Mar 8, 2024 | Keras utilities, data augmentation, autoencoder | |
Mar 15, 2024 | Tensorflow Tensor and Variable, linear classifier in pure Tensorflow, user-defined layer class | |
Mar 22, 2024 | More examples on classification and regression | |
Mar 29, 2024 | Transfer learning, image segmentation | |
Apr 5, 2024 | Recurrent neural networks (RNNs) | |
Apr 12, 2024 | Variational autoencoder | |
Apr 19, 2024 | Generative adversarial networks (GAN) | |
Apr 26, 2024 | Graph neural networks | |
TBA | Project presentation |