<commit_before># NeuralNet

## Artificial Neural Net

Implementation of feed forward artificial neural net in c++(c++11) with back propagation algorithm for supervised learning.


###API:
+ Make new Neural Net:
  * NeuralNet(const std::vector<unsigned> & topology); 
```c++
/*makes new net with 2 input neurons,
                     4 hidden neurons,
                     6 hidden neurons(another hidden layer),
                     1 output neuron
*/
NeuralNet net({2, 4, 6, 1});
```
+ Propagate inputs:
  * std::vector<double> propagate(const std::vector<double> & inputs);
```c++
/*propagate input {0.5, 0.5} through net and get output*/
std::vector<double> output = net.propagate({.5, .5});
```
+ Training Neural Net:
  * void backProp(const std::vector<TrainingExample> & examples, double tol, double alpha);
```c++
/*vector of training examples*/<commit_msg>Modified README<commit_after># NeuralNet

## Artificial Neural Net

Implementation of feed forward artificial neural net in c++(c++11) with back propagation algorithm for supervised learning.


### HOW TO USE:
Just download header file NeuralNet.h and one of the libraries from lib directory:
+ libann.a (static linkinkg)
+ libann.so (dynamic linkinkg)


### API:
+ Make new Neural Net:
  * NeuralNet(const std::vector<unsigned> & topology); 
```c++
/*makes new net with 2 input neurons,
                     4 hidden neurons,
                     6 hidden neurons(another hidden layer),
                     1 output neuron
*/
NeuralNet net({2, 4, 6, 1});
```
+ Propagate inputs:
  * std::vector<double> propagate(const std::vector<double> & inputs);
```c++
/*propagate input {0.5, 0.5} through net and get output*/
std::vector<double> output = net.propagate({.5, .5});
```
+ Training Neural Net:
  * void backProp(const std::vector<TrainingExample> & examples, double tol, double alpha);
```c++
/*vector of training examples*/
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{'dir': 'git-commits-cleaned', 'id': '4343264', 'n_tokens_mistral': 605, 'n_tokens_neox': 535, 'n_words': 200}