課程摘要
機電整合學堂
人工智慧與深度學習
Artificial Intelligence and Deep Learning
負責教師
謝昇憲
學分
3
基本授課節數
54
本課程以由淺入深，循序漸進的教導AI基礎架構，打下AI基礎學習，是踏入AI學習大門必修課程。你將學會資料處理的Python套件(Numpy、Pandas、Scipy、Matplotlib、Seaborn..)；學會用scikit-learn在應用主題中實現機器學習演算法(Regression、Decision Forest、KNN或Kmeans等)、驗證模型績效，並進行參數調校來優化模型；學會用Keras/TensorFlow搭建深度的神經網路，如卷積神經網路(CNN)、遞歸神經網路(RNN)、強化學習(Reinforcement learning)、生成對抗網路(Generative Adversarial Networks)等，以實現人臉辨識、自然語言對話等人工智慧主題。
This course teaches AI infrastructure from the shallower to the deeper, step by step, and lays the foundation for AI learning. It is a compulsory course for stepping into the door of AI learning. You will learn data processing Python suites (Numpy, Pandas, Scipy, Matplotlib, Seaborn...); learn to use scikit-learn to implement machine learning algorithms (Regression, Decision Forest, KNN or Kmeans, etc.) in application topics, and verify models Performance and parameter tuning to optimize the model; learn to use Keras/TensorFlow to build deep neural networks, such as Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Reinforcement Learning, and Generative Confrontation Internet (Generative Adversarial Networks), etc., to realize artificial intelligence topics such as face recognition and natural language dialogue.