머신러닝 및 딥러닝 1 (2022 가을학기)

머신러닝 및 딥러닝 1/ Lecture 1. Intro to Deep Learning & Nearest Neighbor Classifiers

머신러닝 및 딥러닝 1/ Lecture 2. Linear & Softmax Classifiers

머신러닝 및 딥러닝 1/ Lecture 3. Convolutional Neural Networks

Lab 1. Introduction to PyTorch & Neural-net Basics

머신러닝 및 딥러닝 1/ Lecture 4. Convolutional Neural Networks

머신러닝 및 딥러닝 1/ Lecture 5. Training Neural Networks I

Lab 2. Convolutional Neural Networks with Visual Data

머신러닝 및 딥러닝 1/ Lecture 6. Training Neural Networks II

머신러닝 및 딥러닝 1/ Lecture 7. Sequential Data & Recurrent Neural Networks I

머신러닝 및 딥러닝 1/ Lecture 8: Recurrent Neural Networks II (LSTMs & Seq2seq Models)

Lab 3. More on Model Training & Sequential Data Modeling

머신러닝 및 딥러닝 1/ Lecture 9. Attention Mechanism & Transformers

Lab 4. Attention & Transformer Language Models