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深度学习与PyTorch入门实战视频教程

课程涵盖了人工智能的发展历程,基本的数学理论,线性回归,逻辑回归,梯度及梯度下降,损失函数,多分类问题,BatchNorm,卷积神经网络CNN/ResNet,循环神经网络RNN/LSTM,对抗生成网络GAN/WGAN等等,以及对应的PyTorch的实现方式讲解。 学完本课程,学员对当前深度学习的核心内容有了全面深刻的掌握,同时工程能力也得到极大的提升。

详情请前往:https://study.163.com/provider/480000001847407/index.htm?share=2&shareId=480000001847407

课程开发环境:

  • Python 3.6 with Anaconda
  • CUDA 10.0
  • PyTorch 1.0
  • Windows 10

添加:

  1. CIFAR10与ResNet18实战
  2. AE和Variational AE实战

课程介绍

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