雲端運算與巨量資料分析
Cloud Computing and Big Data Analytics
| 節 | 週二 |
|---|---|
2 09:00–09:50 | 雲端運算與巨量資料分析 EDB26 3 節連堂 |
3 10:10–11:00 | |
4 11:10–12:00 |
* 根據陽明交大上課時間表所列
[This course will be taught in Chinese this semester.] See AI everywhere and want to be a master of AI? Need to incorporate data-driven decisions learned from big data into your research? This course provides an overview of machine learning techniques for different kinds of data. You will be introduced to models and algorithms you can use to create machine learning models and to scale those models up on cloud platform to big data problems. At the end of the course, you will be able to: o Design a machine learning approach to leverage the knowledge from data. o Apply machine learning techniques to your own applications. o Know about the state-of-the-art approaches for natural language processing and computer vision. o Analyze big data problems using scalable machine learning algorithms on Spark. o Use cloud platform for building your AIOT applications.
Python
Lab (29%): 5% each for Labs 1-4, 3% each for Labs 5-7 Homework (35%): 5% for HW#1, 10% each for HW #2, #3, and #4 Quiz (6%): randomly happens, 1 pts each Final project (30%) Bonus (up to 6 pts): class participation
| 週次 | 主題 |
|---|---|
| 第 0 週 | Anomaly Detection |
| 第 0 週 | Basic Tools (DNN, CNN, RNN and Transformer)-I (Homework 1) |
| 第 0 週 | Basic Tools (DNN, CNN, RNN and Transformer)-II |
| 第 0 週 | Basic Tools (DNN, CNN, RNN and Transformer)-III |
| 第 0 週 | Cloud Concepts & Technologies |
| 第 0 週 | Course Introduction |
| 第 0 週 | Distributed Algorithm |
| 第 0 週 | Final Project Preparation |
| 第 0 週 | Final Project Presentation |
| 第 0 週 | Generative Models-I |
| 第 0 週 | Generative Models-II |
| 第 0 週 | Hadoop and MapReduce |
| 第 0 週 | Large-scale Machine Learning |
| 第 0 週 | Meta Learning |
| 第 0 週 | Philosophy and Introduction to Deep Learning |
| 第 0 週 | Reinforcement Learning |
| 第 0 週 | Self-supervised Learning |
| 第 0 週 | Spark |
1. Deep Learning with PyTorch by Eli Stevens, Luca Antiga and Thomas Viehmann 2. Data Mining by Aggarwal, Charu C. 3. Learning Spark by Holden Karau, Andy Knowinski, Patrick Wendell & Matei Zaharia
- 時間
- TA 1: 吳易倫 (HW#1, HW#2, HW#3) –w86763777@gmail.com • TA 2:曾偉倫 (HW#4, HW#5) –eric840610.ee02@g2.nctu.edu.tw • TA hour –13-15 every Tuesday @ ED-716
- 聯絡方式
- TEL: (03)571-2121#54530 EMAIL: hhshuai@nctu.edu.tw