SCPY437/SCIP513 Neural Networks and Deep Learning


InstructorChaiwoot Boonyasiriwat
Class HoursThursday, 13.00 - 15.00
Assessmenthomework 60, project 40
SubmissionSubmit HW1, Submit HW2

Tentative Course Schedule

Date Topics
Jan 5, 2026 Introduction to inverse and optimization problems, linear regression [MP4] [PDF]
Jan 8, 2026 Introduction to deep learning, perceptron, neurons, activation functions, loss functions, simple linear regression, steepest descent method [MP4] [PDF]
Jan 12, 2026 Polynomial regression, multiple linear regression, metric space, normed space, inner product space, Hilbert space, Euclidean space, linear functional, Riesz representation theorem [MP4] [PDF]
Jan 15, 2026 Various spaces, Frechet and Gateaux derivatives, batch gradient descent (BGD), stochastic gradient descent (SGD), minibatch gradient descent (MGD) [MP4] [PDF]
Jan 19, 2026 Linear conjugate gradient, underdetermined linear system and a minimum-norm straint, Tikhonov regularization [MP4 (part 1),MP4 (part2)] [PDF]
Jan 22, 2026 multiple linear regression, single-layer perceptron, multilayer perceptron (MLP), parameter vs hyperparameter, data splitting (training, validation, test sets), overfitting problem, ridge regression (L2 regularization), lasso regression (L1 regularization), coordinate descent algorithm [MP4] [PDF]
Jan 29, 2026 Forward propagation, backpropagation, training neural networks [MP4] [PDF]
Feb 5, 2026 Introduction to Keras, SGD and its variants [MP4] [PDF]
Feb 12, 2026 Methods for computing gradients: numerical differentiation, symbolic differentiation, and automatic differentiation [MP4] [PDF]
Feb 19, 2026 Multiple linear regression and MLP using Keras, function approximation and Universal Approximation Theorem [MP4]
Feb 26, 2026 Solving differential equations using neural networks [MP4] [PDF]
Mar 12, 2026 Physics-informed neural networks (continued), statistics and information theory [MP4]
Mar 19, 2026 Classification [MP4] [PDF]
Mar 26, 2026 Image classification, CNN (on-site) [PDF]
Apr 2, 2026 Early-stopping regularization, hyperparameter tuning [MP4]
Apr 9, 2026 Transfer learning and fine tuning, K-fold cross validation, image segmentation, residual neural networks [MP4]
Apr 16, 2026 Autoencoder, variational autoencoder (VAE), Generative adversarial network (GAN)
Apr 23, 2026 Recurrent neural networks (RNNs)
May 7, 2026 Project presentation