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course information of 109 - 2 | 2902 Advanced Artificial Intelligence: Practice and Case Study(人工智慧進階實務)

2902 - 人工智慧進階實務 Advanced Artificial Intelligence: Practice and Case Study


教育目標 Course Target

人工智慧正在改變不同行業,深度學習是近期人工智慧討論度最高的知識領域,本課程將以機器學習、深度學習為基礎,探討不同案例情境下的解決方案,並且透過課程中的演練以及學生小組討論,提出不同切入觀點,讓學生在不同案例學習到不同經驗。課程中不同的章節教學內容皆包含基礎簡介、資料處理工程、實務案例實作與小組討論;資料處理工程主要以資料探勘原理出發,包括資料處理工程觀念,關聯的資料收集、資料清理與篩選、資料儲存與索引,以及資料結構化等,並介紹相關使用工具;章節主要包括深度學習簡介、影像辨識Image Recognition、物件偵測Object Detection、計數分析Object Counting、自動編碼 Autoencoder、社群文字分析、物件追蹤Object Tracking、物件檢測Defect Detection等。課程主要目標培育AI人才實作與經驗。Artificial intelligence is changing different industries, and deep learning is the most discussed knowledge field of artificial intelligence recently. This course will be based on machine learning and deep learning, explore solutions in different case scenarios, and use exercises and student groups in the course Discussions put forward different perspectives so that students can learn different experiences from different cases. The teaching content of different chapters in the course includes basic introduction, data processing engineering, practical case implementation and group discussion; data processing engineering is mainly based on the principles of data exploration, including data processing engineering concepts, related data collection, data cleaning and screening, Data storage and indexing, as well as data structuring, etc., and introduces related tools; chapters mainly include introduction to deep learning, image recognition, image recognition, object detection, counting analysis Object Counting, automatic encoding Autoencoder, community text analysis, objects Track Object Tracking, object detection, Defect Detection, etc. The main goal of the course is to cultivate AI talent implementation and experience.


參考書目 Reference Books

1. 自行編輯投影片教材
2. MIT Deep Learning
By Ian Goodfellow, YoshuaBengio, Aaron Courville
https://github.com/janishar/mit-deep-learning-book-pdf
1. Edit your own slide teaching materials
2. MIT Deep Learning
By Ian Goodfellow, YoshuaBengio, Aaron Courville
https://github.com/janishar/mit-deep-learning-book-pdf


評分方式 Grading

評分項目 Grading Method 配分比例 Grading percentage 說明 Description
作業作業
Homework
50
專題報告專題報告
Special report
40
課堂表現課堂表現
Classroom performance
10

授課大綱 Course Plan

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Course Information

Description

學分 Credit:0-3
上課時間 Course Time:Monday/5,6,7[ST436]
授課教師 Teacher:陳倫奇
修課班級 Class:共選2-4 (雲創學院開)
選課備註 Memo:雲技術、新經濟學程。可修學系:工工、資工、資管、企管、應數、電機。
授課大綱 Course Plan: Open

選課狀態 Attendance

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目前選課人數為 34 人。

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