All previous neural net studies has been transformed from my own neural network codes to tiny-dnn which is c++14 based open source. Please make sure that all applications here are tested on mac os environment.
git clone --recursive https://github.com/supertigim/deep-learning-2nd.git
// to make tiny-dnn the latest version
git submodule foreach git pull origin master
Go to sub folders like cnn, and xor-problem, and read the README.md to build each application.
Don't change unless any improvement happens in your environment
Uncomment defines in config.h
#define CNN_USE_SSE
#define CNN_USE_OMP
#define CNN_USE_GCD
Random generator in random.h
class random_generator {
public:
static random_generator &get_instance() {
static random_generator instance;
return instance;
}
std::mt19937 &operator()() {
set_seed(rd_()); // ADD!!!
return gen_;
}
void set_seed(unsigned int seed) { gen_.seed(seed); }
private:
// avoid gen_(0) for MSVC known issue
// https://connect.microsoft.com/VisualStudio/feedback/details/776456
random_generator() : gen_(3) {}
std::mt19937 gen_;
std::random_device rd_; // ADD!!!
};
1.tiny-dnn online manual
2.comparison between neural network libraries
3.Solving XOR problem using tiny-DNN
4.딥러닝 활용 추천 시스템 개발
5.구글 AI Experiments
6.AI Duet이라는 들은 음악에 맞춰 자동 연주
7.Caffe로 구현한 breakout with DQN
8.python으로 구현한 self driving car
9.8번 설명 사이트
9.Caffe c++ 스터디
MIT