/ml_experiments

papers and implementation

Primary LanguageJupyter Notebook

ml_experiments

Papers: https://docs.google.com/document/d/1IXF3h0RU5zz4ukmTrVKVotPQypChscNGf5k6E25HGvA/edit

Codes

  • auto-encoder network (DONE)

  • constractive auto-encoders (DONE)

  • activation functions how bias changes activation functions (DONE)

  • sparse autoencoders (DONE)

  • denoising autoencoders (DONE)

  • dropout (DONE)

  • spiking neurons (DONE)

  • PCA (DONE)

  • attention (DONE)

  • maxout networks

  • invariance meshure nips09-MeasuringInvariancesDeepNetworks.pdf

  • RNN (DONE)

  • LSTM (DONE)

  • neural turing machine (DONE)

  • word2vec (DONE)

  • batch normalization (DONE)

  • PGM (DONE)

reinforcement learning

  • value iteration (DONE)

  • policy iteration (DONE)

  • monte carlo model free prediction (DONE)

  • monte carlo model free control (DONE)

  • td model free prediction (DONE)

  • td model free control (DONE)

  • q-learning (DONE)

  • sarsa (DONE)

  • off-policy stuff (DONE)

  • value function approximator (DONE)

  • action-value function approximator (DONE)

  • REINFORCE (DONE)

  • softmax policy

  • gaussian policy

  • actor-critic algorithm

  • dyna-Q algorithm

  • exploration and exploitation