Neural Networks - 2
繼續之前的整理。 這次把多層感知機整理一下，其實多層和一層的原理都一樣，都是知道誤差以後，重新調整權重的過程。 其實深度學習也就是把hidden這一層不斷的變多，十幾層甚至幾十層，當然他們的計算方法就和我馬上要說的不太一樣。 假設我現在的神經網絡有三層，input、 hidden、 output。 他們之中分別有三個神經元i， j， k。 我首先知道了最後的結果的誤差，然後對他進行downstre
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相關文章
- 1. Improving Deep Neural Networks[2]
- 2. Neural Networks and Deep Learning -- Class 2: Neural Network Basics
- 3. neural networks and deep learning-chapter1-2
- 4. Course 4-Convolutional Neural Networks--Week 2
- 5. Course 5-Recurrent Neural Networks--Week 2
- 6. Course 2-Improving Deep Neural Networks--Week 2
- 7. Neural Networks
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