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人工智能深度进修框架PyTorch入门实战

人工智能深度进修框架PyTorch入门实战

种别:综合 下载:4次 评论:0次
大年夜小:4.05G 浏览:266次 时间:2019-07-29

PyTorch是业界最灵活,最受好评的框架。本套课程对深度进修算法追根究底、墨守成规式讲解,学员不须要任何机械进修基本,只须要写过代码便可轻松上手。基于计算机视觉和NLP范畴的经典数据集,从零开端结合PyTorch与深度进修算法完成多个案例实战。人工智能深度进修框架PyTorch入门实战课程视频教程下载。

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视频教程文件信息


视频课程简介

目次:/深度进修 Pytorch [3.7G]
      ┣━━1.深度进修框架简介 [48.7M]
      ┃    ┗━━1.lesson1-PyTorch简介.mp4 [48.7M]
      ┣━━2.开辟情况预备 [54.5M]
      ┃    ┗━━2.lesson2-开辟情况预备.mp4 [54.5M]
      ┣━━3.初见深度进修 [208.6M]
      ┃    ┣━━3.lesson3-初探Linear Regression案例-1.mp4 [71.9M]
      ┃    ┣━━4.lesson3-初探Linear Regression案例-2.mp4 [43.1M]
      ┃    ┣━━5.lesson4-PyTorch求解Linear Regression案例.mp4 [35.7M]
      ┃    ┣━━6.lesson5 -手写数字成绩引入1.mp4 [36.7M]
      ┃    ┗━━7.lesson5 -手写数字成绩引入2.mp4 [21M]
      ┣━━4.Pytorch张量操作 [426.4M]
      ┃    ┣━━8.lesson6 根本数据类型1.mp4 [54.4M]
      ┃    ┣━━9.lesson6 根本数据类型2.mp4 [28.2M]
      ┃    ┣━━10.lesson7 创建Tensor 1.mp4 [51.6M]
      ┃    ┣━━11.lesson7 创建Tensor 2.mp4 [44.3M]
      ┃    ┣━━12.lesson8 索引与切片1.mp4 [47.2M]
      ┃    ┣━━13.lesson8 索引与切片2.mp4 [45.4M]
      ┃    ┣━━14.lesson9 维度变换1.mp4 [33.1M]
      ┃    ┣━━15.lesson9 维度变换2.mp4 [40.7M]
      ┃    ┣━━16.lesson9 维度变换3.mp4 [40.8M]
      ┃    ┗━━17.lesson9 维度变换4.mp4 [40.8M]
      ┣━━5.张量高阶操作 [405.3M]
      ┃    ┣━━18.lesson10 Broatcasting 1.mp4 [57.9M]
      ┃    ┣━━19.lesson10 Broatcasting 2.mp4 [46.2M]
      ┃    ┣━━20.lesson11 归并与切割1.mp4 [46.8M]
      ┃    ┣━━21.lesson11 归并与切割2.mp4 [30.8M]
      ┃    ┣━━22.lesson12 根本运算.mp4 [67.1M]
      ┃    ┣━━23.lesson13 数据统计1.mp4 [39.9M]
      ┃    ┣━━24.lesson13 数据统计2.mp4 [54.7M]
      ┃    ┗━━25.lesson14 高阶OP.mp4 [61.9M]
      ┣━━6.随机梯度降低 [286.1M]
      ┃    ┣━━26.lesson16 甚么是梯度1.mp4 [69.2M]
      ┃    ┣━━27.lesson16 甚么是梯度2.mp4 [43.3M]
      ┃    ┣━━28.lesson17 罕见梯度.mp4 [18.4M]
      ┃    ┣━━29.lesson18 激活函数及其梯度1.mp4 [45.5M]
      ┃    ┣━━30.lesson18 激活函数及其梯度2.mp4 [44.4M]
      ┃    ┗━━31.lesson18 激活函数及其梯度3.mp4 [65.3M]
      ┣━━7.感知机梯度传播推导 [258.3M]
      ┃    ┣━━32.lesson19 单一输入感知机1.mp4 [47.4M]
      ┃    ┣━━33.lesson19 多输入Loss层2.mp4 [49.7M]
      ┃    ┣━━34.lesson20 链式轨则.mp4 [39.9M]
      ┃    ┣━━35.lesson21 反向传播.mp4 [82M]
      ┃    ┗━━36.lesson22 优化小实例.mp4 [39.2M]
      ┣━━8.多层感知机与分类器 [353.9M]
      ┃    ┣━━37.lesson24 Logistic Regression.mp4 [47.8M]
      ┃    ┣━━38.lesson25 交叉熵.mp4 [72.8M]
      ┃    ┣━━39.lesson26 多分类实战.mp4 [35M]
      ┃    ┣━━40.lesson27 全连接层.mp4 [52.1M]
      ┃    ┣━━41.lesson28 激活函数与GPU加快.mp4 [39.6M]
      ┃    ┣━━42.lesson29 测试.mp4 [53.8M]
      ┃    ┗━━43.lesson30-Visdom可视化.mp4 [52.8M]
      ┣━━9.过拟合 [262.5M]
      ┃    ┣━━44.lesson31-过拟合与欠拟合.mp4 [42.5M]
      ┃    ┣━━45.lesson32-Train-Val-Test-交叉验证-1.mp4 [45.9M]
      ┃    ┣━━46.lesson32-Train-Val-Test-交叉验证-2.mp4 [32.3M]
      ┃    ┣━━47.lesson33-regularization.mp4 [39M]
      ┃    ┣━━48.lesson34-动量与lr衰减.mp4 [51.5M]
      ┃    ┗━━49.lesson35-early stopping, dropout, sgd.mp4 [51.2M]
      ┣━━10.卷积神经搜集CNN [678.5M]
      ┃    ┣━━50.lesson37-甚么是卷积-1.mp4 [62.8M]
      ┃    ┣━━51.lesson37-甚么是卷积-2.mp4 [39.6M]
      ┃    ┣━━52.lesson38-卷积神经搜集-1.mp4 [41.4M]
      ┃    ┣━━53.lesson38-卷积神经搜集-2.mp4 [62.9M]
      ┃    ┣━━54.lesson38-卷积神经搜集-3.mp4 [35.5M]
      ┃    ┣━━55.lesson39-Pooling&upsample.mp4 [34.1M]
      ┃    ┣━━56.lesson40-BatchNorm-1.mp4 [41.4M]
      ┃    ┣━━57.lesson40-BatchNorm-2.mp4 [51.3M]
      ┃    ┣━━58.lesson41-LeNet5,AlexNet, VGG, GoogLeN.mp4 [49.3M]
      ┃    ┣━━59.lesson41-LeNet5,AlexNet, VGG, GoogLeN.mp4 [40.4M]
      ┃    ┣━━60.lesson42-ResNet,DenseNet-1.mp4 [53.2M]
      ┃    ┣━━61.lesson42-ResNet, DenseNet-2.mp4 [43.6M]
      ┃    ┣━━62.lesson43-nn.Module-1.mp4 [45M]
      ┃    ┣━━63.lesson43-nn.Module-2.mp4 [31.4M]
      ┃    ┗━━64.lesson44-数据加强Data Argumentation.mp4 [46.8M]
      ┣━━11.轮回神经搜集RNN&LSTM [465M]
      ┃    ┣━━65.lesson46-时间序列表示.mp4 [53.5M]
      ┃    ┣━━66.lesson47-RNN道理-1.mp4 [28.4M]
      ┃    ┣━━67.lesson47-RNN道理-2.mp4 [34.9M]
      ┃    ┣━━68.lesson48-RNN Layer应用-1.mp4 [34.2M]
      ┃    ┣━━69.lesson48-RNN Layer应用-2.mp4 [29.9M]
      ┃    ┣━━70.lesson49-时间序列猜想.mp4 [53.3M]
      ┃    ┣━━71.lesson50-RNN练习困难.mp4 [55M]
      ┃    ┣━━72.lesson51-LSTM道理-1.mp4 [33M]
      ┃    ┣━━73.lesson51-LSTM道理-2.mp4 [45.7M]
      ┃    ┣━━74.lesson52-LSTM Layer应用.mp4 [28.4M]
      ┃    ┗━━75.lesson53-情感分类实战.mp4 [68.6M]
      ┗━━12.对抗生成搜集GAN [316.2M]
            ┣━━76.lesson54-数据分布.mp4 [17.4M]
            ┣━━77.lesson55-画家的生长过程.mp4 [28.9M]
            ┣━━78.lesson56-GAN生长.mp4 [23M]
            ┣━━79.lesson57-纳什均衡-D.mp4 [20.4M]
            ┣━━80.lesson58-纳什均衡-G.mp4 [36.6M]
            ┣━━81.lesson59-JS散度的弊病.mp4 [36.8M]
            ┣━━82.lesson60-EM间隔.mp4 [17.2M]
            ┣━━83.lesson61-WGAN与WGAN-GP.mp4 [28.8M]
            ┣━━84.lesson62-G和D完成.mp4 [17.3M]
            ┣━━85.lesson63-GAN实战.mp4 [33.3M]
            ┣━━86.lesson64-GAN练习不稳定.mp4 [20.2M]
            ┗━━87.lesson65-WGAN-GP实战.mp4 [36.3M]

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