Hao Dong

Introduction to Deep Learning (Turing Class)

(2019 Turing Summer Course)

Lecturer: Hao Dong (email: hao.dong(at)pku.edu.cn)

Lecture 1	Introduction	Machine Learning Mathematic Foundation & Basic Concept Neural Network Foundation References: PRML , Deep Learning Book
Lecture 2	Convolutional Neural Networks & Computer Vision	Convolutions, poolings, hierarchical representation learning, subpixel ... History of detection, segmentation, pose estimation, face recognition, tricks and more ...
Lecture 3	Recurrent Neural Networks & Natural Language Processing	World embedding, sequential data, recurrent, LSTM ...
Lecture 4	Generative Adversarial Networks	Vanilla GAN, GAN with encoder Additional Materials: Lecture 13, 14, 15
Lecture 5	GAN Applications	Image synthesis, manipulation, translation ... Additional Materials: Lecture 31, 32, 33
Lecture 6	TensorLayer	Design principle ... GAN practice
Lecture 7	Learning Methods: From data point of view	Supervised, unsupervised, weakly-supervised, semi-supervised learning Additional Materials
Lecture 8	Learning Methods: From mapping point of view	Dual, self-supervised, self-augmented learning Additional Materials
Lecture 9	Learning Methods: others	Transfer learning, meta learning Domain adaptation ... References