Building Deep Learning Applications

NTUT Deep Learning

Week Topic Learning Objectives Slides Code Video Updated
Text Book François Chollet, Deep Learning with Python, Manning, 2017 GitHub
1 Introduction to Deep Learning
  • What is the Machine Learning?
  • Neural Networks, Gradient Descent and Backpropagation
  • State-of-the-arts of deep learning
pdf 2021/2/22
2 Applied Math
  • Basic concepts of Linear Algebra, Probability, Calculus and Optimization
pdf 2021/3/8
3 Introduction to Keras
  • Write Keras code on Google Colab
  • Create a simple Dense Neural Networks
  • Use DNN to solve classification and regression problems
  • Batch, Epoch and Learning rate
pdf IMDB_review
financial_news
house_pricing
2021/3/15
4 Machine Learning Basics
  • Five tribes of Machine Learning
  • KNN, Perceptron, SVM
  • Logistic Regression
  • Linear, Ridge, Lasso Regression and ElasticNet
  • Regularization
  • Overfitting, Cross-validation, Dropout
  • Confusion Matrix, Accuracy, Precision, Recall
pdf classifiers regressors 2021/3/27
5 Convolutional Neural Networks (CNN)
  • Convolution Filters
  • Kernel vs. Filter
  • Max Pooling
  • AlexNet, ResNet, DenseNet, Inception
  • NAS and EfficientNet
pdf 2020/3/31
6-1 Word Embedding pdf 2020/4/7
6-2 RNN & LSTM
  • Recurrent Neural Networks
  • LSTM
  • Temporal CNN
pdf 2020/4/7
6-3 Attention, Transfomer
  • Self-attention
  • Transfomer
  • BERT
pdf 2020/4/7
7 Advanced Keras API
  • Functional API
  • Multi-input and Multi-output model
pdf 2020/4/7
8 Generative Deep Learning
  • Generating Text using LSTM
  • Neural Style Transfer
  • Variational Auto Encoder
  • Generative Adversarial Networks
  • Pix2Pix, CycloneGAN
  • Adversarial Attack
pdf 2020/4/7
9 Object Detection and Segmentation
  • Classification & Detection and Segmentation
  • RCNN, SSD, YOLO, EfficientDet
pdf 2020/5/5
10 Action Recognition
  • Action Recognition and Action Event Detection
  • C3D, TSN, and other Models
pdf 2020/5/5
11 Deep Reinforcement Learning
  • What is Reinforcement Learning?
  • State, Action, Reward and Policy
  • Value-based vs. Policy-based Learning
  • On-policy vs. Off-policy
pdf 2020/6/2
12 Deep Learning on Graphs
  • Graphs and Networks
  • Vertices, Edges, Degree
  • Deep Random Walk
  • Graph Convolutions
pdf 2020/6/9
Fina Project Demo 2020/7/4