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Applied Deep Learning - Syllabus
National Taiwan University, 2016 Fall Semester
Instructor Information
Instructor Email Lecture Location & Hours
Yun-Nung (Vivian) Chen 陳縕儂 [email protected] Thursday 9:10-12:10
General Information
Description
Learning the basic theory of deep learning and how to apply to various applications Expectations and Goals
The students are expected to understand 1) how deep learning works
2) how to frame tasks into deep learning problems
3) how to use deep learning toolkits to implement the designed models, and 4) when and why specific deep learning techniques work for specific problems.
Assignments & Project
5 assignments, 1 group final project, 1 write-up report
Pre-requisites
Required Coding Skills
Proficiency in Python; All assignments will in Python.
Required Courses
College Calculus
Linear Algebra
Probability
Machine Learning (preferred but optional)
Statistics (preferred but optional)
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Course Schedule
Week Topic Reading Assignment
1 (09/15/2016) 中秋假期 2 (09/22/2016) Introduction 3 (09/29/2016) Neural Networks 4 (10/06/2016) Backpropagation
5 (10/13/2016) Word Representation Word Embedding
6 (10/20/2016) Sequential Modeling
7 (10/27/2016) Recursive Neural Networks Sentiment Analysis 8 (11/03/2016) Convolutional Neural Networks
9 (11/10/2016) Recurrent Neural Networks
10 (11/17/2016) Gated Mechanism Natural Language Understanding
11 (11/24/2016) TBA
12 (12/01/2016) Attention Mechanism Language Generation
13 (12/08/2016) Representation Learning Multi-Task Learning 14 (12/15/2016) TBA
15 (12/22/2016) Deep Reinforcement Learning Game Playing 16 (12/29/2016) Deep Reinforcement Learning
17 (01/05/2017) TBA
18 (01/12/2017) Final Project Presentation
Assignment Schedule
Release Date Due Date Subject Time
10/13/2016 10/27/2016 Word Embedding 2 weeks
10/27/2016 11/17/2016 Sentiment Analysis 3 weeks
11/17/2016 12/01/2016 Natural Language Understanding 2 weeks
12/01/2016 12/22/2016 Language Generation 3 weeks
12/22/2016 01/05/2017 Game Playing 2 weeks
