斯坦福李飞飞cs231

invitedtalk：对抗样本和对抗训练.flv [908.45M]

invitedtalk：深度学习的方法及硬件.flv [885.76M]

lecture1 课程介绍-计算机视觉概述.flv [52.90M]

lecture1 课程介绍-课程后勤.flv [161.94M]

lecture1 课程介绍-历史背景.flv [213.19M]

lecture10 循环神经网络1.flv [208.81M]

lecture10 循环神经网络2.flv [196.43M]

lecture10 循环神经网络3.flv [395.15M]

lecture11 识别和分割1.flv [112.23M]

lecture11 识别和分割2.flv [364.58M]

lecture11 图像目标检测和图像分割.flv [373.64M]

lecture12 可视化和理解1.flv [578.23M]

lecture12 可视化和理解2.flv [271.95M]

lecture13 生成模型1.flv [226.94M]

lecture13 生成模型2.flv [337.74M]

lecture13 生成模型3.flv [306.49M]

lecture14 深度增强学习1.flv [177.90M]

lecture14 深度增强学习2.flv [556.21M]

lecture2 图像分类-k最近邻算法.flv [167.09M]

lecture2 图像分类-数据驱动方法.flv [170.05M]

lecture2 图像分类-线性分类1.flv [100.87M]

lecture3 损失函数和优化—损失函数.flv [356.32M]

lecture3 损失函数和优化—优化.flv [183.38M]

lecture4-介绍神经网络-反向传播.flv [396.04M]

lecture4-介绍神经网络-神经网络.flv [137.39M]

lecture5 卷积神经网络-卷积和池化.flv [262.48M]

lecture5 卷积神经网络历史.flv [107.30M]

lecture5 卷积神经网络-视觉之外的卷积神经网络.flv [135.81M]

lecture6 训练神经网络(上)-激活函数.flv [353.38M]

lecture6 训练神经网络(上)-批量归一化.flv [224.44M]

lecture6 训练神经网络(下)-更好地优化.flv [401.72M]

lecture6 训练神经网络(下)-迁移学习.flv [47.35M]

lecture6 训练神经网络(下)-正则化.flv [112.48M]

lecture8 深度学习软件.flv [559.10M]

lecture9 cnn框架.flv [552.79M]