Python深度学习与PyTorch实战教程（网易云课堂）

📁 11.CIFAR10与ResNet实战
    63.lesson43-nn.Module-2.mp4  [31.4 MB]
    61.lesson42-ResNet, DenseNet-2.mp4  [43.6 MB]
    55.lesson39-Pooling&upsample.mp4  [34.1 MB]
    64.lesson44-数据增强Data Argumentation.mp4  [46.8 MB]
    56.lesson40-BatchNorm-1.mp4  [41.4 MB]
    62.lesson43-nn.Module-1.mp4  [45.0 MB]
    58.lesson41-LeNet5,AlexNet, VGG, GoogLeN.mp4  [49.3 MB]
    60.lesson42-ResNet，DenseNet-1.mp4  [53.2 MB]
    59.lesson41-LeNet5,AlexNet, VGG, GoogLeN.mp4  [40.4 MB]
    57.lesson40-BatchNorm-2.mp4  [51.3 MB]
📁 07.感知机梯度传播推导
    36.lesson22 优化小实例.mp4  [39.2 MB]
    34.lesson20 链式法则.mp4  [39.9 MB]
    32.lesson19 单一输出感知机1.mp4  [47.4 MB]
    33.lesson19 多输出Loss层2.mp4  [49.7 MB]
    35.lesson21 反向传播.mp4  [82.0 MB]
📁 13.对抗生成网络GAN
    79.lesson57-纳什均衡-D.mp4  [20.4 MB]
    86.lesson64-GAN训练不稳定.mp4  [20.2 MB]
    78.lesson56-GAN发展.mp4  [23.0 MB]
    81.lesson59-JS散度的弊端.mp4  [36.8 MB]
    82.lesson60-EM距离.mp4  [17.2 MB]
    80.lesson58-纳什均衡-G.mp4  [36.6 MB]
    84.lesson62-G和D实现.mp4  [17.3 MB]
    77.lesson55-画家的成长历程.mp4  [28.9 MB]
    87.lesson65-WGAN-GP实战.mp4  [36.3 MB]
    85.lesson63-GAN实战.mp4  [33.3 MB]
    83.lesson61-WGAN与WGAN-GP.mp4  [28.8 MB]
    76.lesson54-数据分布.mp4  [17.4 MB]
📁 08.多层感知机与分类器
    41.lesson28 激活函数与GPU加速.mp4  [39.6 MB]
    40.lesson27 全连接层.mp4  [52.1 MB]
    39.lesson26 多分类实战.mp4  [35.0 MB]
    43.lesson30-Visdom可视化.mp4  [52.8 MB]
    38.lesson25 交叉熵.mp4  [72.8 MB]
    37.lesson24 Logistic Regression.mp4  [47.8 MB]
    42.lesson29 测试.mp4  [53.8 MB]
📁 02.开发环境准备
    2.lesson2-开发环境准备.mp4  [54.5 MB]
📁 12.循环神经网络RNN&LSTM
    69.lesson48-RNN Layer使用-2.mp4  [29.9 MB]
    72.lesson51-LSTM原理-1.mp4  [33.0 MB]
    73.lesson51-LSTM原理-2.mp4  [45.7 MB]
    66.lesson47-RNN原理-1.mp4  [28.4 MB]
    67.lesson47-RNN原理-2.mp4  [34.9 MB]
    75.lesson53-情感分类实战.mp4  [68.6 MB]
    70.lesson49-时间序列预测.mp4  [53.3 MB]
    68.lesson48-RNN Layer使用-1.mp4  [34.2 MB]
    71.lesson50-RNN训练难题.mp4  [55.0 MB]
    65.lesson46-时间序列表示.mp4  [53.5 MB]
    74.lesson52-LSTM Layer使用.mp4  [28.4 MB]
📁 01.深度学习框架介绍
    1.lesson1-PyTorch介绍.mp4  [48.7 MB]
📁 05.张量高阶操作
    23.lesson13 数据统计1.mp4  [39.9 MB]
    25.lesson14 高阶OP.mp4  [61.9 MB]
    21.lesson11 合并与切割2.mp4  [30.8 MB]
    19.lesson10 Broatcasting 2.mp4  [46.2 MB]
    24.lesson13 数据统计2.mp4  [54.7 MB]
    20.lesson11 合并与切割1.mp4  [46.8 MB]
    18.lesson10 Broatcasting 1.mp4  [57.9 MB]
    22.lesson12 基本运算.mp4  [67.1 MB]
📁 10.卷积神经网络CNN
    53.lesson38-卷积神经网络-2.mp4  [62.9 MB]
    54.lesson38-卷积神经网络-3.mp4  [35.5 MB]
    50.lesson37-什么是卷积-1.mp4  [62.8 MB]
    52.lesson38-卷积神经网络-1.mp4  [41.4 MB]
    51.lesson37-什么是卷积-2.mp4  [39.6 MB]
📁 04.Pytorch张量操作
    09.lesson6 基本数据类型2.mp4  [28.2 MB]
    15.lesson9 维度变换2.mp4  [40.7 MB]
    16.lesson9 维度变换3.mp4  [40.8 MB]
    14.lesson9 维度变换1.mp4  [33.1 MB]
    13.lesson8 索引与切片2.mp4  [45.4 MB]
    11.lesson7 创建Tensor 2.mp4  [44.3 MB]
    17.lesson9 维度变换4.mp4  [40.8 MB]
    10.lesson7 创建Tensor 1.mp4  [51.6 MB]
    12.lesson8 索引与切片1.mp4  [47.2 MB]
    08.lesson6 基本数据类型1.mp4  [54.4 MB]
📁 06.随机梯度下降
    26.lesson16 什么是梯度1.mp4  [69.2 MB]
    28.lesson17 常见梯度.mp4  [18.4 MB]
    27.lesson16 什么是梯度2.mp4  [43.3 MB]
    31.lesson18 激活函数及其梯度3.mp4  [65.3 MB]
    30.lesson18 激活函数及其梯度2.mp4  [44.4 MB]
    29.lesson18 激活函数及其梯度1.mp4  [45.5 MB]
📁 09.过拟合
    48.lesson34-动量与lr衰减.mp4  [51.5 MB]
    45.lesson32-Train-Val-Test-交叉验证-1.mp4  [45.9 MB]
    47.lesson33-regularization.mp4  [39.0 MB]
    49.lesson35-early stopping, dropout, sgd.mp4  [51.2 MB]
    46.lesson32-Train-Val-Test-交叉验证-2.mp4  [32.3 MB]
    44.lesson31-过拟合与欠拟合.mp4  [42.5 MB]
📁 03.初见深度学习
    3.lesson3-初探Linear Regression案例-1.mp4  [71.9 MB]
    7.lesson5 -手写数字问题引入2.mp4  [21.0 MB]
    4.lesson3-初探Linear Regression案例-2.mp4  [43.1 MB]
    5.lesson4-PyTorch求解Linear Regression案例.mp4  [35.7 MB]
    6.lesson5 -手写数字问题引入1.mp4  [36.7 MB]