搜索资源列表
ks_rhinoraid
- ks of elastix boot in anaconda
anaconda-release-notes.txt.tar
- documento completamente inutile per scaricare. non lo fare
celleb_setup
- using CHRP is to trick anaconda into installing FCx into Celleb. -using CHRP is to trick anaconda into installing FCx into Celleb.
svm_series
- 用python实现的SVM回归预测的程序,通过Anaconda实现对机器学习包sklearn的调用。-SVM regression using python to achieve predictable procedures, machine learning package sklearn call by Anaconda.
日常运动数据分析
- 用anaconda内部的科学库进行分析运动数据,并能对数据进行分类。(Anaconda's internal science library is used to analyze the motion data and to classify the data.)
python
- 实现libsvm的python代码实现,这是最新的python实现的开源代码,可以结合anaconda使用(can achieve libsvm's function)
Anaconda使用总结
- Python易用,但用好却不易,其中比较头疼的就是包管理和Python不同版本的问题,特别是当你使用Windows的时候。为了解决这些问题,有不少发行版的Python,比如WinPython、Anaconda等,这些发行版将python和许多常用的package打包,方便pythoners直接使用,此外,还有virtualenv、pyenv等工具管理虚拟环境。 个人尝试了很多类似的发行版,最终选择了Anaconda,因为其强大而方便的
pynlpir-develop
- windos环境下的python的nlpir 安装包,直接解压,pip 即可安装在anaconda上(Under the windos environment python nlpir installation package, directly extract, pip can be installed on anaconda)
DecisionTree
- 利用Anaconda编写的决策树,可用于分类(This decision tree algorithm which is used for classification coded by Anaconda.)
simpleCNN
- 在anaconda+opencv+tensorflow平台下,利用简单的CNN卷积神经网络进行手写字符识别(Under the anaconda+opencv+tensorflow platform, we use simple CNN convolution neural network to handwritten character recognition.)
svm分类鸢尾花数据集
- Three classifications of iris data using SVM based on Anaconda