Neural Network in R培訓

課程代碼

rneuralnet

課程時長

14 時間: 同常來說包括休息是 2天

最低要求

Programming in any programming language recommended .

概觀

本課程介紹了使用R-project軟件將神經網絡應用於現實世界的問題。

Machine Translated

課程簡介

Introduction to Neural Networks

  1. What are Neural Networks
  2. What is current status in applying neural networks
  3. Neural Networks vs regression models
  4. Supervised and Unsupervised learning

Overview of packages available

  1. nnet, neuralnet and others
  2. Differences between packages and itls limitations
  3. Visualizing neural networks

Applying Neural Networks

  • Concept of neurons and neural networks
  • A simplified model of the brain
  • Opportunities neuron
  • XOR problem and the nature of the distribution of values
  • The polymorphic nature of the sigmoidal
  • Other functions activated
  • Construction of neural networks
  • Concept of neurons connect
  • Neural network as nodes
  • Building a network
  • Neurons
  • Layers
  • Scales
  • Input and output data
  • Range 0 to 1
  • Normalization
  • Learning Neural Networks
  • Backward Propagation
  • Steps propagation
  • Network training algorithms
  • range of application
  • Estimation
  • Problems with the possibility of approximation by
  • Examples
  • OCR and image pattern recognition
  • Other applications
  • Implementing a neural network modeling job predicting stock prices of listed

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