SCPY437/SCIP513 Neural Networks and Deep Learning


InstructorChaiwoot Boonyasiriwat
Class HoursThursday, 13.00 - 15.00
Assessmenthomework 60, project 40
SubmissionSubmit 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, optimization algorithms, initialization and normalization
Feb 5, 2026 Hyperparameter tuning, dropout, data augmentation
Feb 12, 2026 Convolution, pooling layers, CNN architectures, classic CNN architectures (LeNet, AlexNet, VGG, ResNet, Inception)
Feb 19, 2026 Applications of CNNs: image classification, object detection, image segmentation
Feb 26, 2026 Transfer learning and fine tuning
Mar 12, 2026 Recurrent neural networks (RNNs), vanishing gradients, GRU, LSTM, word embeddings
Mar 19, 2026 Attention mechanism
Mar 26, 2026 Transformer architecture: self-attention, multi-head attention, positional encoding
Apr 2, 2026 Autoencoder and its applications
Apr 9, 2026 Variational autoencoder (VAE) and its applications
Apr 16, 2026 Generative adversarial network (GAN) and its applications
Apr 23, 2026 Large language models (LLMs)
May 7, 2026 Project presentation