Derek Harter

CSci 574 AI 520 Machine Learning Class Sessions (Thur 02192026)

Derek Harter

C03 Quickstart Guide for Class C++ Programming Assignments

Derek Harter

U01-1 Basic Computing Elements of a Hypothetical Machine Architecture

Derek Harter

C02 Example Assignment Workflow

Derek Harter

L12.5 Introduction to Generative Adversarial Networks

Derek Harter

L12.4 Generating Images with Variational Autoencoders

Derek Harter

L12.3 Neural Style Transfer

Derek Harter

L12.2 DeepDream

Derek Harter

L12.1 Text Generation

Derek Harter

L11.5-2 Sequence-to-Sequence Learning, using a Transformer encoderdecoder

Derek Harter

L11.5-1 Sequence-to-Sequence Learning, using RNN encoderdecoder

Derek Harter

L11.4.3-4 Transformer Architecture Implementing and adding positional encoding

Derek Harter

L11.4.1-2 Transformer Architecture Neural attention and the MultiHead layer

Derek Harter

L11.3.3 Two Approaches for Representing Groups of Words Sequence models and word embeddings

Derek Harter

L11.3.2 Two Approaches for Representing Groups of Words Bag-of-Word Models

Derek Harter

L11.1-2 NLP and Preparing Text Data

Derek Harter

L09.4 Interpreting what Convnets Learn

Derek Harter

L10.4 Advanced Use of Recurrent Neural Networks

Derek Harter

L10.3 Understanding Recurrent Neural Networks

Derek Harter

L10.1-2 Timeseries Tasks and a Temperature Forecasting Example

Derek Harter

L09.3.5 A Mini Xception-like Model Example

Derek Harter

L09.3 Modern Convnet Architecture Patterns

Derek Harter

L09.1-2 Computer Vision Tasks and an Image Segmentation Example

Derek Harter

L08.3 Leveraging a Pretrained Model

Derek Harter

L08.2 Training a Convnet from Scratch on a Small Dataset

Derek Harter

L08.1 Introduction to Convnets

Derek Harter

L07.4 Writing your own Training and Evaluation Loops

Derek Harter

L07.3 Metrics, Callbacks and TensorBoard

Derek Harter

L07.2 Keras APIs for Building Models

Derek Harter

L05.4 Improving Model Generalization

Derek Harter