手动寻找的1500张左右的小型飞机数据集，包含了客机，战斗机，直升机等等常见的飞机类别。

手动寻找的鱼类小型数据集，包含了很多种鱼的普适类别，图片质量有保障

PyTorch介绍及入门pdf，英文的，讲得很详细。

The CAS-PEAL face database has been constructed under the sponsors of National Hi-Tech Program and ISVISION by the Face Recognition Group of JDL, ICT, CAS. The goals to create the PEAL face database include: providing the worldwide researchers of FR community a large-scale Chinese face database for training and evaluating their algorithms; facilitating the development of FR by providing large-scale face images with different sources of variations, especially Pose, Expression, Accessories, and Lighting (PEAL); advancing the state-of-the-art face recognition technologies aiming at practical applications especially for the oriental. Currently, the CAS-PEAL face database contains 99,594 images of 1040 individuals (595 males and 445 females) with varying Pose, Expression, Accessory, and Lighting (PEAL). For each subject, 9 cameras spaced equally in a horizontal semicircular shelf are setup to simultaneously capture images across different poses in one shot. Each subject is also asked to look up and down to capture 18 images in another two shots. We also considered 5 kinds of expressions, 6 kinds accessories (3 glasses, and 3 caps), and 15 lighting directions. This face database is now partly made available (a subset named by CAS-PEAL-R1, contain 30,900 images of 1040 subjects) for research purpose only on a case-by-case basis only. JDL is serving as the technical agent for distribution of the database and reserves the copyright of all the images in the database.

caffe imagenet的均值文件。

吴恩达深度学习deeplearning第五课第一周课后测验及编程作业（含答案）

深度神经网络加速与压缩概览 ................................................................................

一种识别交通标志的多层次化神经网络结构,主要用来识别交通标志，数据集市德国交通标志数据集，该文论是2011年Lecun发表的

吴恩达深度学习（deeplearning.ai）一到五课全部课后编程题（第三课没有编程作业，第四课资源太大，已上传网盘分享）

斯坦福大学-深度学习-cs230-DeepLearning-官方知识点总结PDF，以图表形式呈现，全面简单易懂