Deep Learning course for humanists

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  • 1. Introduction
    • 1.1 Introduction
    • 1.2 Environment Setup
  • 2. Perceptron
    • 2.1 Foundation block of Neural Network—Perceptron
    • 2.2 Iris Classification
  • 3. Multilayer Perceptron
    • 3.1 Multilayer Perceptron
    • 3.2 Activate Function
  • 4. Forward Propagation
    • 4.1 How the single pass through the network—Forward Propagation
    • 4.2 Matrix
    • 4.3 Apply matrix to neural network computation
    • 4.4 Design the Output Layer
  • 5. Training Neural Networks
    • 5.1 How well does the neural network predict?—Loss Function
    • 5.2 Learning to minimize error—Gradient Descent Method

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