課 程 概 述
Course Description

課程編碼
Course Code
中文課程名稱
Course Name (Chinese)
英文課程名稱
Course Name (English)
總學分數
Credits
總時數
Hours
3102102 深度學習TensorFlow實務 Deep Learning with TensorFlow 3.0 3
中文概述
Chinese Description
人工智慧(Artificial Intelligence)正以現在進行式,廣泛應用於大眾日常生活,改善人類生產力,影響我們文明價值。人工智慧領域中,最核心的技術就是深度學習 (Deep Learning, DL),它是從機械學習 (Machine Learning, ML) 的基本概念,延伸到深度神經網路 (Deep Neural Network, DNN) 的原理和應用技術,具自動地萃取特徵的功能,是當今科技界最熱門的研究項目。本課程介紹深度學習的基礎概念、數學模型演算法,與工程實作原理,瞭解深度學習與TensorFlow開源框架(Open Source Framework)的關鍵實作技術。課程建置TensorFlow運作框架環境,利用精簡程式碼及模型描述文件,設計一個完整的神經網路系統,進而深入淺出進行深度學習技術的實作與應用。本課程涵蓋原理介紹及實作實習,包含: 1.)機械學習、深度學習及神經網路原理介紹, 2.)TensorFlow框架特性及安裝實習, 3.)常用的數學模型演算法 CNN、RNN、及RBM實作, 4.)強化學習介紹, 5.)深度學習應用範例實習。
英文概述
English Description
Artificial Intelligence (AI) has been widely used in our daily life. It can not only improve human productivity but also enhance the value of human civilization. In the field of AI, the core technology is Deep Learning (DL), which extends from the basic concept of Machine Learning (ML) to the principle of Deep Neural Network (DNN). This technology, with the ability to automatically extract features, is now the popular research topic in the scientific and technological world. This course introduces the basic concepts of DL, mathematical model algorithms, and engineering implementation principles, and understands the key implementation techniques of DL with the TensorFlow Open Source Framework (OSF). The course experiment builds the TensorFlow development environment with streamlined codes and model description files to design a complete DNN. This course introduces the principles and practical aspects of: 1.) ML, DL and DNN, 2.) The features of TensorFlow and OSF installation, 3.) Implem

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