DeepLearning W1-Introduction

Introduction

Analyze the major trends driving the rise of deep learning, and give examples of where and how it is applied today.

学习目标

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• Discuss the major trends driving the rise of deep learning.
• Explain how deep learning is applied to supervised learning
• List the major categories of models (CNNs, RNNs, etc.), and when they should be applied
• Assess appropriate use cases for deep learning

What is a Neural Network?

Supervised Learning with Neural Networks

• 定义：
  • 由训练资料中学到或创建一个模式（函数 / learning model），并依此模式推测新的实例
• neural networks
  • RNN (Recurrent Neural Network) 适用于：
  • sequence data，for example：
    • language translate
  • CNN（convolutional neural networks）

Why is Deep Learning taking off?

scale drives deep learning progress

Influencing Factors（影响因素）

• Data
• Computation
• Algorithms
  • 类型
    • Sigmoid激活函数（图一）
    • ReLU激活函数（图二）
      • stands for Rectified Linear Unit
  • 对比
    • switching from sigmoid to ReLU activation functions allows faster training

相关资料

• Standard notations for Deep Learning

• PPT