百度飞桨学习python机器学习、深度学习资料

[{"title":"（ 38 个子文件 35.42MB ） 百度飞桨学习python机器学习、深度学习资料","children":[{"title":"00 百度飞桨学习资料","children":[{"title":"数据集","children":[{"title":"鸢尾花分类","children":[{"title":"iris.data <span style='color:#111;'> 4.44KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"【计算机视觉】13.实践：基于TSN的视频分类.pdf <span style='color:#111;'> 2.86MB </span>","children":null,"spread":false},{"title":"【计算机视觉】4.实践：基于深度神经网络的宝石分类.pdf <span style='color:#111;'> 605.15KB </span>","children":null,"spread":false},{"title":"密码000123.txt <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"【计算机视觉】10.实践：PaddleSeg-BiseNet.pdf <span style='color:#111;'> 3.45MB </span>","children":null,"spread":false},{"title":"【机器学习】飞桨与python入门操作：实践-海量文件遍历、图像直方图统计、文本词频统计.pdf <span style='color:#111;'> 951.77KB </span>","children":null,"spread":false},{"title":"【机器学习】飞桨高层API的实践.pdf <span style='color:#111;'> 582.13KB </span>","children":null,"spread":false},{"title":"【机器学习】GRU：实践-情感分类的另一种方法.pdf <span style='color:#111;'> 724.96KB </span>","children":null,"spread":false},{"title":"【计算机视觉】9.实践：YOLOV3.pdf <span style='color:#111;'> 2.36MB </span>","children":null,"spread":false},{"title":"【计算机视觉】8.实践：PaddleDetection-Faster RCNN.pdf <span style='color:#111;'> 3.12MB </span>","children":null,"spread":false},{"title":"【机器学习】python复杂操作：实践-爬虫与数据分析.pdf <span style='color:#111;'> 505.25KB </span>","children":null,"spread":false},{"title":"【计算机视觉】7.实践：基于ResNet的CIFAR10数据分类 .pdf <span style='color:#111;'> 825.75KB </span>","children":null,"spread":false},{"title":"【机器学习】飞桨预训练模型：实践-图像分类+文本分类的Fine-Tuning.pdf <span style='color:#111;'> 572.89KB </span>","children":null,"spread":false},{"title":"【机器学习】全连接神经网络：实践-房价预测.pdf <span style='color:#111;'> 460.51KB </span>","children":null,"spread":false},{"title":"【计算机视觉】14.实践：基于ECO的视频分类.pdf <span style='color:#111;'> 503.30KB </span>","children":null,"spread":false},{"title":"【计算机视觉】1.实践：飞浆与python入门操作.pdf <span style='color:#111;'> 951.39KB </span>","children":null,"spread":false},{"title":"【机器学习】自然语言处理前沿应用：实践-基于PaddleHub实现文本审核＋分本生成.pdf <span style='color:#111;'> 800.85KB </span>","children":null,"spread":false},{"title":"【机器学习】VGGNet原理：实践-中草药分类.pdf <span style='color:#111;'> 1.14MB </span>","children":null,"spread":false},{"title":"【计算机视觉】11.实践：基于U-Net的宠物分割.pdf <span style='color:#111;'> 205.66KB </span>","children":null,"spread":false},{"title":"【计算机视觉】15.实践：基于GAN的手写数字生成.pdf <span style='color:#111;'> 392.21KB </span>","children":null,"spread":false},{"title":"【计算机视觉】3.理论：计算机视觉概述.pdf <span style='color:#111;'> 4.47MB </span>","children":null,"spread":false},{"title":"【机器学习】Word2Vec实现：实践-基于CBOW和Skip-gram实现Word2Vec.pdf <span style='color:#111;'> 368.71KB </span>","children":null,"spread":false},{"title":"【机器学习】LSTM：实践-谣言检测.pdf <span style='color:#111;'> 662.00KB </span>","children":null,"spread":false},{"title":"机器学习分类算法：实践-鸢尾花分类与文本奶粉类.pdf <span style='color:#111;'> 1.06MB </span>","children":null,"spread":false},{"title":"【机器学习】图像预处理与分类方法：实践-宝石分类.pdf <span style='color:#111;'> 821.23KB </span>","children":null,"spread":false},{"title":"【机器学习】ResNet-50原理：实践-CIFAR10数据集分类.pdf <span style='color:#111;'> 885.04KB </span>","children":null,"spread":false},{"title":"【机器学习】自然语言处理基础：实践-文本数据预处理.pdf <span style='color:#111;'> 626.40KB </span>","children":null,"spread":false},{"title":"【计算机视觉】2.实践：python复杂操作.pdf <span style='color:#111;'> 505.36KB </span>","children":null,"spread":false},{"title":"【计算机视觉】6.实践：基于VGG-16 的中草药识别.pdf <span style='color:#111;'> 1.08MB </span>","children":null,"spread":false},{"title":"【机器学习】卷积神经网络：实践-美食分类.pdf <span style='color:#111;'> 545.96KB </span>","children":null,"spread":false},{"title":"【机器学习】循环神经网络：实践-情感分类.pdf <span style='color:#111;'> 380.39KB </span>","children":null,"spread":false},{"title":"【计算机视觉】18.实践：基于CycleGaN的图像风格迁移.pdf <span style='color:#111;'> 275.66KB </span>","children":null,"spread":false},{"title":"【计算机视觉】5.实践：基于卷积神经网络的美食识别.pdf <span style='color:#111;'> 276.23KB </span>","children":null,"spread":false},{"title":"【机器学习】计算机视觉前沿应用：实践-基于PaddleHub实现目标检测＋图像风格迁.pdf <span style='color:#111;'> 1.46MB </span>","children":null,"spread":false},{"title":"机器学习聚类算法：实践-鸢尾花分类的另一种方法.pdf <span style='color:#111;'> 767.75KB </span>","children":null,"spread":false},{"title":"【计算机视觉】16.实践：基于DCGAN的人脸图像生成.pdf <span style='color:#111;'> 329.99KB </span>","children":null,"spread":false},{"title":"【计算机视觉】17.实践：基于Pix2Pix的图像翻译.pdf <span style='color:#111;'> 415.79KB </span>","children":null,"spread":false},{"title":"【计算机视觉】12.实践：基于DeepLabV3 Plus的宠物分割.pdf <span style='color:#111;'> 373.96KB </span>","children":null,"spread":false}],"spread":false}],"spread":true}]