深度学习之神经网络(CNN&RNN&GAN)算法原理+实战 - 带源码课件
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 深度学习之神经网络(CNN&RNN&GAN)算法原理+实战 - 带源码课件https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第9章 对抗神经网络
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第3章 卷积神经网络
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第8章 图像生成文本
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第7章 循环神经网络
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第6章 图像风格转换
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第4章 卷积神经网络进阶
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第11章 课程总结
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第5章 卷积神经网络调参
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第10章 自动机器学习网络-AutoML
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第1章 课程介绍
https://cdn.ldstatic.com/images/emoji/twemoji/file_folder.png?v=15 第2章 神经网络入门
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 资料.zip
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-2 卷积神经网络（1）.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-3 卷积神经网络（2）.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-1 神经网络进阶.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 3-4 卷积神经网络实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-4 深度卷积对抗生成网络DCGAN(2)_深度学习之神经网络RNNGAN算法原理实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-9 文本生成图像Text2Img_深度学习之神经网络RNNGAN算法原理实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-7 无配对图像翻译CycleGAN(2)_深度学习之神经网络RNNGAN算法原理实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-10 对抗生成网络总结_深度学习之神经网络RNNGAN算法原理实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-1 对抗生成网络原理.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-5 图像翻译Pix2Pix_深度学习之神经网络RNNGAN算法原理实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-3 反卷积.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-8 多领域图像翻译StarGAN_深度学习之神经网络RNNGAN算法原理实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-6 无配对图像翻译CycleGAN(1)_深度学习之神经网络RNNGAN算法原理实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-16 DCGAN训练算子实现_深度学习之神经网络RNNGAN算法原理实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-14 DCGAN判别实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-13 DCGAN生成器实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-11 DCGAN实战引.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-2 深度卷积对抗生成网络DCGAN(1).mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-12 数据生成器实现_深度学习之神经网络RNNGAN算法原理实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-17 训练流程实现与效果展示_深度学习之神经网络RNNGAN算法原理实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 9-15 DCGAN计算图构建实现与损失函数实现_深度学习之神经网络RNNGAN算法原理实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-3 长短期记忆网络.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-1 序列式问题.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-4 基于LSTM的文本分类模型(TextRNN与HAN).mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-7 数据预处理之分词.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-15 指标计算与梯度算子实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-14 计算图实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-13 计算图输入定义.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-19 循环神经网络总结.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-2 循环神经网络.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-10 超参数定义.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-6 RNN与CNN融合解决文本分类.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-17 LSTM单元内部结构实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-9 实战代码模块解析.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-12 数据集封装.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-8 数据预处之词表生成与类别表生成.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-16 训练流程实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-5 基于CNN的文本分类模型(TextCNN).mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-18 TextCNN实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 7-11 词表封装与类别封装.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-18 计算图构建-图片与词语embedding.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-21 文本生成图像问题引入与本节课总结.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-20 训练流程代码.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-5 Show and Tell模型.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-15 ImageCaptionData类封装-图片特征读取.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-6 Show attend and Tell 模型.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-3 Encoder-Decoder框架与Beam Search算法生成文本.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-4 Multi-Modal RNN模型.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-12 输入输出文件与默认参数定义.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-19 计算图构建-rnn结构实现、损失函数与训练算子实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-17 计算图构建-辅助函数实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-9 数据介绍，词表生成.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-7 Bottom-up Top-down Attention模型.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-11 图像特征抽取(2)-Inception3预训练模型抽取图像特征.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-10 图像特征抽取(1)-文本描述文件解析.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-2 图像生成文本评测指标.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-8 图像生成文本模型对比与总结.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-14 文本描述转换为ID表示.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-1 图像生成文本问题引入.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-13 词表载入.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 8-16 ImageCaptionData类封装-批数据生成.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 11-1 课程总结.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-11 批归一化实战（2）.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-7 actiation-initializer-optimizer-实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-9 图像增强实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-4 Tensorboard实战（1） (1).mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-2 激活函数到调参技巧（1）.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-8 图像增强api使用.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-6 fine-tune-实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-10 批归一化实战（1）.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-4 Tensorboard实战（1）.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-3 激活函数到调参技巧（2）.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 5-1 adagrad_adam.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-3 卷积神经网络进阶（inception-mobile-net）.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-2 卷积神经网络进阶（ggnet-Resnet）.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-7 Inception-mobile_net（2）.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-1 卷积神经网络进阶（alexnet）.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-5 GG-ResNet实战（2）.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-4 GG-ResNet实战（1）.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 4-6 Inception-mobile_net（1）.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-2 卷积神经网络的能力.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-5 GG16预训练模型读取函数封装.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-12 图像风格转换3算法.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-10 图像风格转换效果展示.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-8 图像风格转换计算图构建与损失函数计算.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-4 GG16预训练模型格式.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-7 图像风格转换算法定义输入与调用GG-Net.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-9 图像风格转换训练流程代码实现.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-6 GG16模型搭建与载入类的封装.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-1 卷积神经网络的应用.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-11 图像风格转换2算法.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 6-3 图像风格转换1算法.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 10-5 自动网络结构搜索算法三_深度学习之神经网络RNNGAN算法原理实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 10-3 自动网络结构搜索算法一的分布式训练_深度学习之神经网络RNNGAN算法原理实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 10-4 自动网络结构搜索算法二_深度学习之神经网络RNNGAN算法原理实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 10-2 自动网络结构搜索算法一_深度学习之神经网络RNNGAN算法原理实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 10-1 AutoML引入_深度学习之神经网络RNNGAN算法原理实战.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 2-7 神经元实现（二分类逻辑斯蒂回归模型实现）.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 2-5 数据处理与模型图构建(1).mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 2-4 梯度下降.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 2-2 神经元-逻辑斯底回归模型.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 2-1 机器学习、深度学习简介.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 2-6 数据处理与模型图构建(2).mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 2-3 神经元多输出.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 2-8 神经网络实现（多分类逻辑斯蒂回归模型实现）.mp4
https://cdn.ldstatic.com/images/emoji/twemoji/page_facing_up.png?v=15 1-1 课程导学.mp4
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