Course Code: rneuralnet
Duration: 14 hours
Prerequisites:

Programming 在任何推荐的编程语言中。

Overview:

本課程介紹如何使用 R-project 軟件將神經網絡應用於現實世界中的問題。

Course Outline:

Neural Networks 簡介

  1. Neural Networks 是什麼
  2. 目前神經網絡的應用現狀
  3. Neural Networks 與回歸模型的比較
  4. 監督式與非監督式學習

可用套件概述

  1. nnet、neuralnet 及其他
  2. 套件之間的差異及其限制
  3. 神經網絡的可視化

應用 Neural Networks

  • 神經元與神經網絡的概念
  • 大腦的簡化模型
  • 神經元的機會
  • XOR 問題與值的分佈特性
  • Sigmoidal 函數的多態性
  • 其他激活函數
  • 神經網絡的構建
  • 神經元連接的概念
  • 神經網絡作為節點
  • 建立網絡
  • 神經元
  • 層
  • 比例
  • 輸入與輸出數據
  • 範圍 0 到 1
  • 標準化
  • 學習 Neural Networks
  • 反向傳播
  • 傳播步驟
  • 網絡訓練算法
  • 應用範圍
  • 估算
  • 近似可能性問題
  • 範例
  • OCR 與圖像模式識別
  • 其他應用
  • 實施神經網絡模型預測上市股票價格
Sites Published:

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