深度學習

臺北科技大學 115-1 學期課程，課號 366152。

• 學期：115-1
• 授課教師：伊柏文
• 學分：3
• 選修
• 上課時段：週三 5、6、7 節

課程大綱

1. 深度學習簡介、2.神經網路基礎、3.訓練深度神經網路、4.深度學習架構介紹、 5.卷積神經網路、6. 循環神經網路與序列建模、7. 模型評估與性能指標、8.應用案例分析。 1. Introduction to Deep Learning 2. Fundamentals of Neural Networks 3. Training Deep Neural Networks 4. Introduction to Deep Learning Frameworks 5. Convolutional Neural Networks 6. Recurrent Neural Networks (RNNs) and Sequence Modeling 7. Model Evaluation and Performance Metrics 8. Application Case Studies

課程進度

Week 1-2. Introduction to Deep Learning Week 3-4. Fundamentals of Neural Networks Week 4-6. Deep Neural Networks Week 7-9. Convolutional Neural Networks Week 10-12. Computer Vison Week 13-14 . Recurrent Neural Networks (RNNs) Week 15. Generative Models Week 15-16. Application Case Studies Week 17-18. Final project presentation

評量方式

Quizzes & Assignments : 40 % Labs / Mini Projects: 20 % Attendance : 10 % Final Project : 30 %

教材

【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 References : 1. Goodfellow, I., Bengio, Y. & Courville, A.: Deep Learning. 2016, MIT. 2. Anirudh Koul, Siddha Ganju, Meher Kasam: Practical Deep Learning for Cloud, Mobile, and Edge: Real-World AI & Computer-Vision Projects Using Python, Keras & TensorFlow 1st Edition