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Functions1,905 in github.com/lazyprogrammer/machine_learning_examples

⨍ Functions 1,905◇ Types & classes 254↳ Endpoints 4
↓ 2 callersMethodget_params
(self)
cnn_class2/tf_resnet.py:67
↓ 2 callersFunctionget_sentences
()
rnn_class/brown.py:19
↓ 2 callersFunctionget_spiral
()
ann_class2/util.py:34
↓ 2 callersFunctionget_spiral
()
numpy_class/exercises/ex8.py:13
↓ 2 callersFunctionget_spiral
()
svm_class/util.py:40
↓ 2 callersFunctionget_stories
(f)
nlp_class3/memory_network.py:51
↓ 2 callersMethodget_value_prediction
(self, state, sess)
rl2/a3c/worker.py:178
↓ 2 callersFunctionget_words
(sentence)
nlp_class2/markov.py:93
↓ 2 callersFunctionget_xor
()
svm_class/util.py:75
↓ 2 callersFunctiongram_matrix
(img)
cnn_class2/style_transfer2.py:30
↓ 2 callersFunctionhop
(query, story)
nlp_class3/memory_network.py:350
↓ 2 callersFunctionimresize
(arr, sz)
unsupervised_class3/util.py:28
↓ 2 callersMethodinit
(self)
rl3/es_flappy.py:85
↓ 2 callersFunctioninit_filter
(shape, poolsz)
cnn_class/cnn_tf_plot_filters.py:34
↓ 2 callersFunctioninit_filter
(shape, poolsz)
cnn_class/cnn_tf.py:34
↓ 2 callersMethodinit_random
(self, X)
hmm_class/hmmc_tf.py:29
↓ 2 callersMethodinit_vars
(self)
rl2/mountaincar/pg_tf_random.py:114
↓ 2 callersFunctioninit_weight
(M1, M2)
ann_class2/batch_norm_theano.py:17
↓ 2 callersFunctioninit_weight_and_bias
(M1, M2)
cnn_class/cifar.py:17
↓ 2 callersFunctionlink
(src, dst)
cnn_class2/make_limited_datasets.py:9
↓ 2 callersFunctionlist2pdict
(ts)
hmm_class/frost.py:68
↓ 2 callersMethodload
(self, name)
tf2.0/keras_trader.py:323
↓ 2 callersMethodload
(self, name)
tf2.0/mlp_trader.py:303
↓ 2 callersFunctionload_img
(filepath)
cnn_class2/siamese.py:30
↓ 2 callersFunctionload_img_and_preprocess
(path, shape=None)
cnn_class2/style_transfer3.py:35
↓ 2 callersMethodlog_likelihood
(self, x)
hmm_class/hmmc_scaled_concat.py:179
↓ 2 callersMethodlog_likelihood
(self, x)
hmm_class/hmmc_scaled_concat_diag.py:177
↓ 2 callersMethodlog_likelihood_multi
(self, X)
hmm_class/hmmc_scaled_concat.py:200
↓ 2 callersMethodlog_likelihood_multi
(self, X)
hmm_class/hmmc_scaled_concat_diag.py:234
↓ 2 callersMethodlog_likelihood_multi
(self, X)
hmm_class/hmmc.py:226
↓ 2 callersMethodlog_likelihood_multi
(self, X)
hmm_class/hmmc_concat.py:198
↓ 2 callersMethodlog_likelihood_multi
(self, X)
hmm_class/hmmd.py:159
↓ 2 callersMethodlog_likelihood_multi
(self, X)
hmm_class/hmmd_scaled.py:132
↓ 2 callersFunctionloglikelihood
(X, Z, W)
bayesian_ml/2/em.py:25
↓ 2 callersFunctionmake_atari
(env_id)
rl3/a2c/atari_wrappers.py:219
↓ 2 callersFunctionmake_poly
(x, D)
supervised_class2/bias_variance_demo.py:23
↓ 2 callersFunctionmake_train_op
Use gradients from local network to update the global network
rl2/a3c/worker.py:65
↓ 2 callersFunctionmax_dict
(d)
rl/monte_carlo_no_es.py:61
↓ 2 callersFunctionmaybe_make_dir
(directory)
tf2.0/rl_trader.py:85
↓ 2 callersFunctionmaybe_make_dir
(directory)
tf2.0/keras_trader.py:92
↓ 2 callersFunctionmaybe_make_dir
(directory)
tf2.0/mlp_trader.py:77
↓ 2 callersFunctionmaybe_make_dir
(directory)
rl/linear_rl_trader.py:48
↓ 2 callersFunctionmaybe_make_dir
(directory)
pytorch/rl_trader.py:80
↓ 2 callersFunctionminimize
(fn, epochs, batch_shape)
cnn_class2/style_transfer2.py:47
↓ 2 callersFunctionmse
(p, t)
recommenders/itembased.py:162
↓ 2 callersFunctionmy_tokenizer
(s)
nlp_class/sentiment.py:56
↓ 2 callersFunctionone_hot_encode
(X, K)
recommenders/rbm_tf_k.py:29
↓ 2 callersFunctionone_step_attention
(h, st_1)
nlp_class3/attention.py:238
↓ 2 callersMethodpartial_fit
(self, X, Y)
rl2/mountaincar/pg_theano.py:199
↓ 2 callersFunctionplay_game
(p1, p2, env, draw=False)
rl/tic_tac_toe.py:374
↓ 2 callersFunctionplay_multiple_episodes
(env, T, params)
rl3/gym_review.py:31
↓ 2 callersFunctionplay_multiple_episodes
(env, T, pmodel, gamma, print_iters=False)
rl2/mountaincar/pg_tf_random.py:197
↓ 2 callersFunctionplay_multiple_episodes
(env, T, pmodel, gamma, print_iters=False)
rl2/mountaincar/pg_theano_random.py:164
↓ 2 callersFunctionplay_multiple_episodes
(env, T, params)
rl2/cartpole/random_search.py:37
↓ 2 callersFunctionplay_one_episode
(env, params)
rl2/cartpole/save_a_video.py:23
↓ 2 callersFunctionplot_decision_boundary
(X, model)
supervised_class2/util.py:13
↓ 2 callersFunctionplot_decision_boundary
(model, resolution=100, colors=('b', 'k', 'r'))
svm_class/util.py:118
↓ 2 callersFunctionplot_image
(x, Q, title)
bayesian_ml/1/nb.py:109
↓ 2 callersFunctionplot_k_means
(X, K, index_word_map, max_iter=20, beta=1.0, show_plots=True)
unsupervised_class/books.py:100
↓ 2 callersMethodpost
(self)
supervised_class/app.py:28
↓ 2 callersMethodposterior_predictive_sample
(self, X)
unsupervised_class3/vae_tf.py:231
↓ 2 callersFunctionpredict
(X, W1, b1, W2, b2)
ann_class/xor_donut.py:35
↓ 2 callersFunctionpredict
(i, m)
recommenders/userbased.py:111
↓ 2 callersFunctionpredict
(i, u)
recommenders/itembased.py:113
↓ 2 callersFunctionpredict
(P_Y_given_X)
ann_logistic_extra/logistic_softmax_train.py:40
↓ 2 callersFunctionpredict
(P_Y_given_X)
ann_logistic_extra/ann_train.py:44
↓ 2 callersMethodpredict
(self, X)
unsupervised_class3/autoencoder_tf.py:65
↓ 2 callersMethodpredict
(self, states)
rl2/atari/dqn_tf.py:243
↓ 2 callersMethodpredict
(self, X)
rl2/atari/dqn_theano.py:309
↓ 2 callersMethodpredict
(self, X)
rl2/mountaincar/pg_theano.py:205
↓ 2 callersMethodpredict
(self, X)
rl2/mountaincar/pg_tf.py:165
↓ 2 callersMethodpredict
(self, s)
rl2/mountaincar/td_lambda.py:56
↓ 2 callersMethodpredict
(self, s)
rl2/cartpole/q_learning.py:78
↓ 2 callersMethodpredict
(self, s)
rl2/cartpole/q_learning_bins.py:64
↓ 2 callersMethodpredict
(self, X)
rl2/cartpole/dqn_tf.py:115
↓ 2 callersMethodpredict
(self, X)
rl2/cartpole/dqn_theano.py:135
↓ 2 callersMethodpredict
(self, s)
rl2/cartpole/td_lambda.py:57
↓ 2 callersMethodpredict
(self, s, a)
rl/cartpole_gym0.19.py:55
↓ 2 callersMethodpredict
(self, s, a)
rl/approx_control.py:69
↓ 2 callersMethodpredict
(self, X)
unsupervised_class2/autoencoder_tf.py:76
↓ 2 callersMethodpredict
(self, X)
svm_class/svm_smo.py:252
↓ 2 callersMethodpredict
(self, X)
supervised_class/perceptron.py:63
↓ 2 callersMethodpredict_all_actions
(self, s)
rl/cartpole_gym0.19.py:60
↓ 2 callersMethodpredict_all_actions
(self, s)
rl/cartpole.py:61
↓ 2 callersMethodpredict_proba
(self, X)
bayesian_ml/2/probit.py:51
↓ 2 callersMethodprior_predictive_sample_with_probs
(self)
unsupervised_class3/vae_tf.py:235
↓ 2 callersMethodpull
(self)
ab_testing/ucb1_starter.py:25
↓ 2 callersMethodpull
(self)
rl/ucb1_starter.py:25
↓ 2 callersMethodpull
(self)
rl/ucb1.py:25
↓ 2 callersMethodpull
(self)
rl/comparing_explore_exploit_methods.py:23
↓ 2 callersFunctionrandom_normalized
(d1, d2)
hmm_class/hmmd_theano.py:17
↓ 2 callersFunctionrandom_normalized
(d1, d2)
hmm_class/hmmd.py:16
↓ 2 callersFunctionrandom_normalized
(d1, d2)
hmm_class/hmmd_scaled.py:15
↓ 2 callersFunctionrearrange
(X)
cnn_class/cnn_tf_plot_filters.py:39
↓ 2 callersFunctionrearrange
(X)
cnn_class/cnn_tf.py:39
↓ 2 callersFunctionrearrange
(X)
cnn_class/keras_example.py:31
↓ 2 callersFunctionrepeat_frame
(frame)
rl2/a3c/worker.py:41
↓ 2 callersMethodreset
(self)
rl3/flappy2envs.py:38
↓ 2 callersMethodreset
(self)
rl3/a2c/subproc_vec_env.py:84
↓ 2 callersMethodreset
(self)
tf2.0/rl_trader.py:166
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