2017.4.17-2017.4.21文本分类，XGBoost综述，图像识别

内容简介：2017.4.17-2017.4.21文本分类，XGBoost综述，图像识别

http://alias-i.com/lingpipe/  LingPipe is tool kit for processing text using computational linguistics.

http://svmlight.joachims.org/ 基于svm做文本分类

http://adrem.ua.ac.be/~tmartin/  svm jni java接口

https://github.com/antoniosehk/keras-tensorflow-windows-installation  windows上安装基于tensoflow-gpu的keras深度学习包

http://thegrandjanitor.com/  机器学习

http://www.wsdm-conference.org/2017/accepted-papers/  wsdm 2017 accepted papers

https://www.slideshare.net/BhaskarMitra3/neural-text-embeddings-for-information-retrieval-wsdm-2017

https://github.com/laura-dietz/tutorial-utilizing-kg

http://colah.github.io/posts/2015-08-Understanding-LSTMs/

https://cmusatyalab.github.io/openface/

https://eliasvansteenkiste.github.io/ Predicting lung cancer

https://brage.bibsys.no/xmlui/handle/11250/2433761 Tree Boosting With XGBoost - Why Does XGBoost Win "Every" Machine Learning Competition?

https://github.com/YaronBlinder/MIMIC-III_readmission/ Predicting 30-day ICU readmissions from the MIMIC-III database

https://github.com/caffe2/caffe2  facebook  开源深度学习框架 caffe2

MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications https://arxiv.org/abs/1704.04861

https://zhuanlan.zhihu.com/p/24322376 欺诈盛宴：百万黑产军团，两千万手机号，瓜分百亿蛋糕

以上就是本文的全部内容，希望本文的内容对大家的学习或者工作能带来一定的帮助，也希望大家多多支持 码农网

查看所有标签

本站部分资源来源于网络，本站转载出于传递更多信息之目的，版权归原作者或者来源机构所有，如转载稿涉及版权问题，请联系我们。