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文件名称:Dive into DL Pytorch 源代码

  • 所属分类：
    书籍源码
  • 标签属性：
  • 上传时间：
    2022-06-24
  • 文件大小：
    20.85mb
  • 已下载：
    2次
  • 提 供 者：
    nnnn123
  • 相关连接：
    无
  • 下载说明：
    别用迅雷下载，失败请重下，重下不扣分！
修正介绍说明

介绍说明－－下载内容来自于网络，使用问题请自行百度

Dive into DL Pytorch源代码，jupyter notebook
(系统自动生成,下载前可以参看下载内容)

下载文件列表

压缩包 : Dive-into-DL-PyTorch-master.zip 列表
Dive-into-DL-PyTorch-master/
Dive-into-DL-PyTorch-master/.github/
Dive-into-DL-PyTorch-master/.github/ISSUE_TEMPLATE/
Dive-into-DL-PyTorch-master/.github/ISSUE_TEMPLATE/bug_report.md
Dive-into-DL-PyTorch-master/.gitignore
Dive-into-DL-PyTorch-master/LICENSE
Dive-into-DL-PyTorch-master/code/
Dive-into-DL-PyTorch-master/code/chapter02_prerequisite/
Dive-into-DL-PyTorch-master/code/chapter02_prerequisite/2.2_tensor.ipynb
Dive-into-DL-PyTorch-master/code/chapter02_prerequisite/2.3_autograd.ipynb
Dive-into-DL-PyTorch-master/code/chapter03_DL-basics/
Dive-into-DL-PyTorch-master/code/chapter03_DL-basics/3.10_mlp-pytorch.ipynb
Dive-into-DL-PyTorch-master/code/chapter03_DL-basics/3.11_underfit-overfit.ipynb
Dive-into-DL-PyTorch-master/code/chapter03_DL-basics/3.12_weight-decay.ipynb
Dive-into-DL-PyTorch-master/code/chapter03_DL-basics/3.13_dropout.ipynb
Dive-into-DL-PyTorch-master/code/chapter03_DL-basics/3.16_kaggle-house-price.ipynb
Dive-into-DL-PyTorch-master/code/chapter03_DL-basics/3.1_linear-regression.ipynb
Dive-into-DL-PyTorch-master/code/chapter03_DL-basics/3.2_linear-regression-scratch.ipynb
Dive-into-DL-PyTorch-master/code/chapter03_DL-basics/3.3_linear-regression-pytorch.ipynb
Dive-into-DL-PyTorch-master/code/chapter03_DL-basics/3.5_fashion-mnist.ipynb
Dive-into-DL-PyTorch-master/code/chapter03_DL-basics/3.6_softmax-regression-scratch.ipynb
Dive-into-DL-PyTorch-master/code/chapter03_DL-basics/3.7_softmax-regression-pytorch.ipynb
Dive-into-DL-PyTorch-master/code/chapter03_DL-basics/3.8_mlp.ipynb
Dive-into-DL-PyTorch-master/code/chapter03_DL-basics/3.9_mlp-scratch.ipynb
Dive-into-DL-PyTorch-master/code/chapter04_DL_computation/
Dive-into-DL-PyTorch-master/code/chapter04_DL_computation/4.1_model-construction.ipynb
Dive-into-DL-PyTorch-master/code/chapter04_DL_computation/4.2_parameters.ipynb
Dive-into-DL-PyTorch-master/code/chapter04_DL_computation/4.4_custom-layer.ipynb
Dive-into-DL-PyTorch-master/code/chapter04_DL_computation/4.5_read-write.ipynb
Dive-into-DL-PyTorch-master/code/chapter04_DL_computation/4.6_use-gpu.ipynb
Dive-into-DL-PyTorch-master/code/chapter05_CNN/
Dive-into-DL-PyTorch-master/code/chapter05_CNN/5.10_batch-norm.ipynb
Dive-into-DL-PyTorch-master/code/chapter05_CNN/5.11_resnet.ipynb
Dive-into-DL-PyTorch-master/code/chapter05_CNN/5.12_densenet.ipynb
Dive-into-DL-PyTorch-master/code/chapter05_CNN/5.1_conv-layer.ipynb
Dive-into-DL-PyTorch-master/code/chapter05_CNN/5.2_padding-and-strides.ipynb
Dive-into-DL-PyTorch-master/code/chapter05_CNN/5.3_channels.ipynb
Dive-into-DL-PyTorch-master/code/chapter05_CNN/5.4_pooling.ipynb
Dive-into-DL-PyTorch-master/code/chapter05_CNN/5.5_lenet.ipynb
Dive-into-DL-PyTorch-master/code/chapter05_CNN/5.6_alexnet.ipynb
Dive-into-DL-PyTorch-master/code/chapter05_CNN/5.7_vgg.ipynb
Dive-into-DL-PyTorch-master/code/chapter05_CNN/5.8_nin.ipynb
Dive-into-DL-PyTorch-master/code/chapter05_CNN/5.9_googlenet.ipynb
Dive-into-DL-PyTorch-master/code/chapter06_RNN/
Dive-into-DL-PyTorch-master/code/chapter06_RNN/6.2_rnn.ipynb
Dive-into-DL-PyTorch-master/code/chapter06_RNN/6.3_lang-model-dataset.ipynb
Dive-into-DL-PyTorch-master/code/chapter06_RNN/6.4_rnn-scratch.ipynb
Dive-into-DL-PyTorch-master/code/chapter06_RNN/6.5_rnn-pytorch.ipynb
Dive-into-DL-PyTorch-master/code/chapter06_RNN/6.7_gru.ipynb
Dive-into-DL-PyTorch-master/code/chapter06_RNN/6.8_lstm.ipynb
Dive-into-DL-PyTorch-master/code/chapter07_optimization/
Dive-into-DL-PyTorch-master/code/chapter07_optimization/7.1_optimization-intro.ipynb
Dive-into-DL-PyTorch-master/code/chapter07_optimization/7.2_gd-sgd.ipynb
Dive-into-DL-PyTorch-master/code/chapter07_optimization/7.3_minibatch-sgd.ipynb
Dive-into-DL-PyTorch-master/code/chapter07_optimization/7.4_momentum.ipynb
Dive-into-DL-PyTorch-master/code/chapter07_optimization/7.5_adagrad.ipynb
Dive-into-DL-PyTorch-master/code/chapter07_optimization/7.6_rmsprop.ipynb
Dive-into-DL-PyTorch-master/code/chapter07_optimization/7.7_adadelta.ipynb
Dive-into-DL-PyTorch-master/code/chapter07_optimization/7.8_adam.ipynb
Dive-into-DL-PyTorch-master/code/chapter08_computational-performance/
Dive-into-DL-PyTorch-master/code/chapter08_computational-performance/8.1_hybridize.ipynb
Dive-into-DL-PyTorch-master/code/chapter08_computational-performance/8.3_auto-parallelism.ipynb
Dive-into-DL-PyTorch-master/code/chapter08_computational-performance/8.4_model.pt
Dive-into-DL-PyTorch-master/code/chapter08_computational-performance/8.4_multiple-gpus.ipynb
Dive-into-DL-PyTorch-master/code/chapter09_computer-vision/
Dive-into-DL-PyTorch-master/code/chapter09_computer-vision/9.1_image-augmentation.ipynb
Dive-into-DL-PyTorch-master/code/chapter09_computer-vision/9.2_fine-tuning.ipynb
Dive-into-DL-PyTorch-master/code/chapter09_computer-vision/9.3_bounding-box.ipynb
Dive-into-DL-PyTorch-master/code/chapter09_computer-vision/9.4_anchor.ipynb
Dive-into-DL-PyTorch-master/code/chapter10_natural-language-processing/
Dive-into-DL-PyTorch-master/code/chapter10_natural-language-processing/10.12_machine-translation.ipynb
Dive-into-DL-PyTorch-master/code/chapter10_natural-language-processing/10.3_word2vec-pytorch.ipynb
Dive-into-DL-PyTor

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