教學大綱與進度

課程基本資料：

學年期	課號	課程名稱	階段	學分	時數	修	教師	班級	人	撤	備註
110-2	302416	深度學習應用開發實務	1	3.0	3	★	賴冠廷	電子所 電資外生所	71	2	◎電子所與電資外生所合開

教學大綱與進度：

教師姓名	賴冠廷
Email	ktlai@ntut.edu.tw
最後更新時間	2022-02-23 22:04:39
課程大綱	The goal of this course is to give students a broad overview of state-of-the-art deep learning algorithms, and teach students how to develop deep learning applications by hands-on coding examples. Most examples taught in this class are based on the TensorFlow framework. We will cover many different fields including image classification, object detection, natural language processing, reinforcement learning and generative adversarial networks. The syllabus is listed as follows: • Number and Character recognition • Image Classification for 1000 categories • Object Detection for 9000 objects • Convolutional Neural Networks (CNNs) • Recurrent Neural Networks (RNN) • Long-Short Term Memory (LSTM) • Stock Price Prediction using LSTM • Attention, Transformer, BERT, and GPT-3 • Generative Adversarial Networks (GANs) • Deep Reinforcement Learning
課程進度	1. Intro to Deep Learning 2. Applied Math (Linear Algebra, Probability, Calculus) 3. Machine Learning Basics 4. TensorFlow & Keras 5. Convolutional Neural Networks 6. Advanced Keras API 7. NLP & Word Embedding 8. RNN/LSTM and Stock Price Prediction 9. Attention & Transformer, BERT, GPT-3 10. Generative Adversarial Networks (GANs) 11. Object Detection and Segmentation 12. Deep Reinforcement Learning
評量方式與標準	Homework (40%), Midterm and Final Exam (40%), Final Project (20%), Quizzes (5%)
使用教材、參考書目或其他	【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】 使用外文原文書：是 1. Francois Chollet, “Deep Learning with Python, ” Manning, 2017 2. Ian Goodfellow, Yoshua Bengio, and Aaron Courville, “Deep Learning,” MIT Press, 2017 3. Latest publications on CVPR, NIPS, ICML, AAAI, ICLR Website: http://www.aiotlab.org/teaching/dl_app.html
課程諮詢管道
備註	因應疫情發展，本學期教學及授課方式請依照學校網頁所公布之訊息為準： (https://oaa.ntut.edu.tw/p/404-1008-98622.php?Lang=zh-tw) All quizzes, exams and homework will be made online using Microsoft Teams. For final project, students will need to submit a YouTube video. Any announcements will be posted in Microsoft Teams. Website: http://www.aiotlab.org/teaching/dl_app.html FB Group: https://www.facebook.com/groups/2231151677158713