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cv-interview-implementation's Introduction

计算机视觉算法岗常见算法的实现

What I cannot create, I do not understand.

内容

  1. 常见网络层的实现(卷积层线性层)。
  2. 常见损失函数(Adversarial Losses, L1 Loss, Smooth L1 Loss, L2 Loss, MSE Loss, Triplet Loss, Cross Entropy Loss, Negative Log Likelihood Loss),距离度量,散度以及相似性函数的实现。
  3. 常见指标的实现(Inception Score, Fréchet Inception Distance)。
  4. 常见机器学习算法的实现(多层感知机)。
  5. 经典网络的实现(DCGAN, VGG16, ResNet)。
  6. 常见归一化方法的实现(BatchNorm)。
  7. 常见优化器的实现(SGD, Momentum, Adagrad, RMSprop, Adam, AdamW)。
  8. 常见正则化方法的实现(R1 正则化)。
  9. 常见可视化方法的实现。
  10. 常见激活函数的实现。
  11. 常见图像处理的实现。
  12. 常见的权重初始化方法的实现。

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