资源列表
BayesianNetwork
- 在机器学习中，本代码实现用贝叶斯的方法进行分类(In machine learning, this code is implemented with Bayesian classification)
局部算子
- matlab的LBP代码,最基础的图像处理算法(the local binary pattern code)
scikit-learn-docs
- 学习机器学习的利器，非常适合初学者，书写的十分详细(Learning machine learning tool)
Python语言及其应用(美Lubanovic 2016)
- python语言及其应用电子版，非常实用，可供初学者进行参考阅读(python language and its application electronic version, very practical, for beginners to read)
sourceCode
- 用python 语言结合DNN简单实现语音增强(DNN speech enhancement)
线性回归
- 采用python实现的简单的线性回归程序，从数据读取开始，有实验的结果(The program is linear_regression used python and result .)
keras-master
- python 工具包 keras 的学习。(python keras learning)
逻辑回归
- 用python实现逻辑回归，附带评价机制和结果，并有具体说明(Logical regression, incidental evaluation mechanism and results)
bp
- 简单的bp神经网络代码，通过python编写，很适合学习应用(Simple BP neural network code, written by python, it is suitable for learning applications)
lenet5
- 此例为神经网络中lenet5的框架，适合学习图像识别、cnn的人学习(This is the framework of the lenet5 neural network, image recognition, suitable for learning to learn CN)
TC
- 一个基于传统向量空间模型文本分类方法对比(A comparison of text categorization methods based on traditional vector space model)
test
- tensorflow测试 计算mnist识别准确率 以及计算时间(tensorflow test Calculate the MNIST recognition accuracy and calculation time)