# NN_Test

**Repository Path**: axellance/NN_Test

## Basic Information

- **Project Name**: NN_Test
- **Description**: This project contains some neural network code
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-04-20
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# NN_Test
**This project contains some neural network code**  
**Note: Clone this repository to E:/GitCode/ in windows**
- neural network code(C++)
	- Perceptron
	- BP(Back Propagation)
	- CNN(Convolutional Neural Networks)
	- Linear Regression(gradient descent、least squares)
	- Naive Bayes Classifier(sex classification)
	- Logistic Regression(gradient descent, Batch/Mini Batch)
	- KNN(K-Nearest Neighbor, classification)
	- PCA(Principal Components Analysis)
	- single hidden layer(two categories)
	- K-Means
	- Decision Tree(CART)
- mathematical formula's implement with C++
	- Linear Algebra
		- transpose
		- determinant
		- adjoint matrix
		- inverse matrix
		- norm(vector、matrix)
		- eigenvalues/eigenvectors(real symmetric matrix)
		- SVD(Singular Value Decomposition)
		- pseudoinverse
		- trace
	- Probability
		- mean、variance、standard deviation
		- covariance matrix
	- Activation Function
		- logistic sigmoid function
		- softplus function
		- ReLU(rectified linear unit)
		- Leaky ReLUs(leaky rectified linear units)
		- ELUs(Exponential linear units)
		- softmax function
	- Layers
		- Dropout
	- common algorithm
		- Brute Force(string match)
- open source library's usage(C++)
	- tiny-cnn [GitHub](https://github.com/nyanp/tiny-cnn)
	- tiny-dnn [GitHub](https://github.com/tiny-dnn/tiny-dnn)
	- libsvm [GitHub](https://github.com/cjlin1/libsvm)
	- OpenCV 3.3 [GitHub](https://github.com/opencv/opencv)
		- Logistic Regression
		- Support Vector Machines(SVM)
		- KNN(K-Nearest Neighbor)
		- Decision Tree
		- PCA(Principal Components Analysis)
		- k-means
- Python code(support windows and linux platform)
	- KNN(K-Nearest Neighbor)
	- Decision Tree(CART)
	- PCA(Principal Components Analysis)
	- k-means
- Database convert to Images or Images conver to Database
	- MNIST
	- CIFAR10/CIFAR100
	- ORL Faces Database

**The project support platform:** 
- windows7/10 64 bits: It can be directly build with VS2013 in windows7/10 64bits.
- Linux:
	- DatasetToImage support cmake build(file position: prj/linux_cmake_DatasetToImage)
	- Math support cmake build(file position: prj/linux_cmake_Math)
	- tiny-cnn support cmake build(file position: prj/linux_cmake_tiny-cnn)
	- tiny-dnn support cmake build(file position: prj/linux_cmake_tiny-dnn)
	- NN support cmake build(file position: prj/linux_cmake_NN)

**Windows VS Screenshot:**  
![](https://github.com/fengbingchun/NN_Test/blob/master/prj/x86_x64_vc12/Screenshot.png)


**Blog:** [fengbingchun](http://blog.csdn.net/fengbingchun/article/category/780354)