Machine learning과 관련된 여러가지 알고리즘을 정리합니다.
11월 23일 ~ 26일 사이에 40개 완료 예정 예상기간 X
- Residual network
- Batch normalization
- Backpropagation
- Shuffle net
- Variational autoencoder
- Attention
- Mobile net
- BEGAN
- CRELU
- ReLU
- DCGAN
- InfoGAN
- Dropout
- Gaussian mixture
- Expetation maximization
- Softmax
- LSTM
- GRU
- Resnext
- Fractal net
- BLEU
- Inception module
- Weight diverge
- REINFORCE algorithm
- Actor-critic
- Model-free RL
- Bayes theorem
- K-means clustering
- Bossting
- Decision tree
- Principal component analysis
- Eigenvalue
- Linear regression
- Binomial distribution
- Support vector machin
- p-value
- Adaboost
- Markov decision process
- Hidden Markov model
- Q-learning
- Dynamic programming
- Law of large numbers
- Singular value decomposition
- Curese of dimension
- Wasserstein distance
- Kullback-Leibler divergence
- L2 norm
- A3C
- Cycle GAN
- Monte Carlo tree search
- Capsule networks
- r-CNN
- Faster r-CNN
- YOLO algorithm
- Wavenet
- Wavelet
- SARSA algorithm
유튜브 : https://www.youtube.com
추천 유튜버 : https://www.youtube.com/channel/UCML9R2ol-l0Ab9OXoNnr7Lw
위키 : https://en.wikipedia.org/wiki/Main_Page
도서 : http://book.naver.com/bookdb/book_detail.nhn?bid=4753048