AI 研究模組

Unit 1_Mathemetics for Machine Learning(馬清文副教授): This course is design to provides on some essential mathematical foundations on which machine learning and artificial intelligence are based. Topics include 1) algebra foundations such as equations, functions, and graphs; 2) differential calculus such as derivatives and optimization; 3) linear algebra such as vector-matrix multiplication and matrix decomposition and; 4) statistics, probability and basic information theory. We will also write python codes to explore the concepts and technologies that are introduced in this course. Unit 2_基礎課程: git, docker, cloud and linux 基礎(魏澤人副教授): 介紹常用軟體開發工具以及相關的概念,包含 * 以 git 為主的版本控制系統, * docker 及虛擬化技術,包含在 windows 上的 ws * 雲端及相關的網路服務概念 * Linux 命令列、 ssh, X 的使用及概念 目的是加速實驗及軟體開發的效率,評量方式以實際操作及心得分享為主。 Unit 3_AI with Minmax and Monte Carlo tree search(魏澤人副教授): 內容包含 * minmax 簡介 * alpha beta pruning * MTD(f), Null Move, Principal Variation Search * Monte Carlo Tree Search * Exploration and exploitation 目的為了解這類工具的特性,以結合或了解其他技術如深度學習的基礎(如Alpha Go) Unit 4_Deep Learning Hardware and Software(馬清文副教授): Deep learning algorithms require heavy computations. To deal with the demand, judiciously design hardware and software are built. In this course, we will talk about popular software platforms such as Tensorflow/keras and Pytorch. We explore the basic difference between these software platforms and develop the idea of how to choose one from them for our own works. Regarding the deep learning hardware, we will take a look at deep leaning accelerators which are used in edge AI and well-known among many AI chip startups. Unit 5_多旋翼無人機原理與系統(邱俊誠教授): * Flight principle * Introduction for Multirotor Copters * Flight weather Unit 6_智慧感測(林勻蔚助理教授): 本課程將介紹如何蒐集環境資訊、記錄與追蹤,之後可做為大數據分析之用途。 Unit 7_多旋翼無人機智慧飛控與模擬飛行(歐陽盟教授): * Flight Dynamics and Flight power modules of Multirotor Copters * Multisensing and Communication modules of Multirotor Copters * Flight Control and Simulation of Multirotor Copters

Unit 1_Mathemetics for Machine Learning(馬清文副教授): 1. Computer programming skill, especially Python and C. 2. College linear algebra, calculus and probability concepts. Unit 2_基礎課程: git, docker, cloud and linux 基礎(魏澤人副教授): 無 Unit 3_AI with Minmax and Monte Carlo tree search(魏澤人副教授): 無 Unit 4_Deep Learning Hardware and Software(馬清文副教授): 1. Computer programming skill, especially writing Python and C programs. 2. Computer architecture concepts such as CPU, instruction set, memory, data bus, etc. Unit 5_多旋翼無人機原理與系統(邱俊誠教授): 無 Unit 6_智慧感測(林勻蔚助理教授): Python初階能力、簡易電路製作 Unit 7_多旋翼無人機智慧飛控與模擬飛行(歐陽盟教授): 無

Unit 1_Mathemetics for Machine Learning(馬清文副教授): Web resource: 1. Essential math for machine learning https://www.edx.org/course/essential-math-for-machine-learning-python-editi-2 Unit 2_基礎課程: git, docker, cloud and linux 基礎(魏澤人副教授): 無 Unit 3_AI with Minmax and Monte Carlo tree search(魏澤人副教授): 無 Unit 4_Deep Learning Hardware and Software(馬清文副教授): 1. Stanford CS231 2020 lecture slides: http://cs231n.stanford.edu/slides/2020/lecture_6.pdf 2. Stanford CS231 2017 Youtube video: Lecture 8 | Deep Learning Software: https://www.youtube.com/watch?v=6SlgtELqOWc&list=PL3FW7Lu3i5JvHM8ljYj-zLfQRF3EO8sYv&index=9&t=0s 3. nVidia Deep learning accelerator http://nvdla.org/ 4. NVDLA Deep Learning Inference Compiler is Now Open Source https://devblogs.nvidia.com/nvdla/ Unit 5_多旋翼無人機原理與系統(邱俊誠教授): 無 Unit 6_智慧感測(林勻蔚助理教授): 課程有助教可解答學生疑難問題。 Unit 7_多旋翼無人機智慧飛控與模擬飛行(歐陽盟教授): 無

Unit 1_Mathemetics for Machine Learning(馬清文副教授): Homeworks: 100% Unit 2_基礎課程: git, docker, cloud and linux 基礎(魏澤人副教授): 教學方式主要為概念講解,現場實際操作,實際演練作業及心得分享。 Unit 3_AI with Minmax and Monte Carlo tree search(魏澤人副教授): 教學方式為理論講解,簡單實驗,最後為設計一個簡單的棋類 AI。 Unit 4_Deep Learning Hardware and Software(馬清文副教授): Homeworks: 100% Unit 5_多旋翼無人機原理與系統(邱俊誠教授): Quiz Unit 6_智慧感測(林勻蔚助理教授): 以每一課堂單元作業進行評分。 Unit 7_多旋翼無人機智慧飛控與模擬飛行(歐陽盟教授): 1. One quiz 2. Simulation flight

Unit 1_Mathemetics for Machine Learning(馬清文副教授): 1. Marc Peter Deisenroth, A. Aldo Faisal, and Cheng Soon Ong. MATHEMATICS FOR MACHINE LEARNING. Cambridge University Press, 2020 2. Goodfellow and Yoshua Bengio and Aaron Courville. Deep Learning. Chapter 2,3,4,5. MIT Press, 2016 Unit 2_基礎課程: git, docker, cloud and linux 基礎(魏澤人副教授): No textbook. Unit 3_AI with Minmax and Monte Carlo tree search(魏澤人副教授): No textbook. Unit 4_Deep Learning Hardware and Software(馬清文副教授): No textbook. Unit 5_多旋翼無人機原理與系統(邱俊誠教授): No textbook. Unit 6_智慧感測(林勻蔚助理教授): No textbook. Unit 7_多旋翼無人機智慧飛控與模擬飛行(歐陽盟教授): No textbook.

地點

Unit 1_Mathemetics for Machine Learning(馬清文副教授): CM 507 Unit 2_基礎課程: git, docker, cloud and linux 基礎(魏澤人副教授): Unit 3_AI with Minmax and Monte Carlo tree search(魏澤人副教授): Unit 4_Deep Learning Hardware and Software(馬清文副教授): CM 507 Unit 5_多旋翼無人機原理與系統(邱俊誠教授): Unit 6_智慧感測(林勻蔚助理教授): CM422 Unit 7_多旋翼無人機智慧飛控與模擬飛行(歐陽盟教授):

時間

Unit 1_Mathemetics for Machine Learning(馬清文副教授): On appointment Unit 2_基礎課程: git, docker, cloud and linux 基礎(魏澤人副教授): On appointment Unit 3_AI with Minmax and Monte Carlo tree search(魏澤人副教授): On appointment Unit 4_Deep Learning Hardware and Software(馬清文副教授): On appointment Unit 5_多旋翼無人機原理與系統(邱俊誠教授): On appointment Unit 6_智慧感測(林勻蔚助理教授): 週四下午13:00~16:00 Unit 7_多旋翼無人機智慧飛控與模擬飛行(歐陽盟教授): On appointment

聯絡方式

Unit 1_Mathemetics for Machine Learning(馬清文副教授): machingwen@nctu.edu.tw Unit 2_基礎課程: git, docker, cloud and linux 基礎(魏澤人副教授): tjw@nctu.edu.tw Unit 3_AI with Minmax and Monte Carlo tree search(魏澤人副教授): tjw@nctu.edu.tw Unit 4_Deep Learning Hardware and Software(馬清文副教授): machingwen@nctu.edu.tw Unit 5_多旋翼無人機原理與系統(邱俊誠教授): chiou@mail.nctu.edu.tw Unit 6_智慧感測(林勻蔚助理教授): jyneda@gmail.com Unit 7_多旋翼無人機智慧飛控與模擬飛行(歐陽盟教授): oym@nctu.edu.tw