支持向量机的代码

基于模态分析理论和神金网络的损伤识别算法，包含架构和实际的应用程序说明。(Damage identification program)

说明：  机器学习第二版书籍源码，文件较大，分章节上传(This is the code repository for Python Machine Learning - Second Edition, published by Packt. It contains all the supporting project files necessary to work through the book from start to finish.)

说明：  深度学习正在为广泛的行业带来革命性的变化。对于许多应用来说，深度学习通过做出更快和更准确的预测，证明其已经超越人类的预测。本书提供了自上而下和自下而上的方法来展示深度学习对不同领域现实问题的解决方案。这些应用程序包括计算机视觉、自然语言处理、时间序列预测和机器人。(Deep learning is bringing revolutionary changes to a wide range of industries. For many applications, deep learning proves to be beyond human prediction by making faster and more accurate predictions. This book provides top-down and bottom-up approaches to demonstrate deep learning solutions to practical problems in different areas. These applications include computer vision, natural language processing, time series prediction and robotics.)

this program about and word

超级好用，建议有一定前段基础和Python知识的人下载。亲测通过。

基于python语言读取Micaps格式数据，包括地面、高空、格点数据等类型。(Read Micaps format data based on Python language)

New firmware gx 6605s

python学习最好书籍，里面的例子个个精彩（算法一绝），确保任何人能一周之内掌握世界上书写最优美的编程语言。(python learning the best books containing excellent examples of each (one must algorithm), ensure that any person within a week to master the world's most beautiful writing programming language.)

GAC模型代码，很好的matlab代码，希望大家多多分享(GAC model code, good code matlab)

 ------------| EnhanceNet | ------------This is a pre-trained reference implementation of ENet-PAT from "EnhanceNet:Single Image Super-Resolution through Automated Texture Synthesis" for amagnification ratio of 4.It comes with a script which takes care of installing all necessary packagesinside a virtual environment, i.e. all installations take place inside thefolder and can be simply uninstalled by deleting the folder. Advanced usersmay install the packages directly (see FAQ section).Please note that the code has only been tested on Linux and OS/X.If you use this code as part of a publication, please cite:@inproceedings{enhancenet,  title={{EnhanceNet}:         Single Image Super-Resolution through Automated Texture Synthesis},  author={Sajjadi, Mehdi~S.~M. and Sch{"o}lkopf, Be