├── .github ├── labeler.yml └── workflows │ └── stale.yml ├── .gitignore ├── .pylintrc ├── .travis.yml ├── CONTRIBUTING.md ├── README.md ├── chainer ├── README.md ├── chlab-01-1-basics.py ├── chlab-02-1-linear_regression.py ├── chlab-05-2-logistic_regression_mnist.py ├── chlab-10-2-mnist_nn.py └── chlab-10-3-mnist_modern.py ├── data-01-test-score.csv ├── data-02-stock_daily.csv ├── data-03-diabetes.csv ├── data-04-zoo.csv ├── ipynb ├── lab-01-basics.ipynb ├── lab-02-1-linear_regression.ipynb ├── lab-02-2-linear_regression_feed.ipynb ├── lab-02-3-linear_regression_tensorflow.org.ipynb ├── lab-03-1-minimizing_cost_show_graph.ipynb ├── lab-03-2-minimizing_cost_gradient_update.ipynb ├── lab-03-3-minimizing_cost_tf_optimizer.ipynb ├── lab-03-X-minimizing_cost_tf_gradient.ipynb ├── lab-05-1-logistic_regression.ipynb ├── lab-08-tensor_manipulation.ipynb ├── lab-10-6-mnist_nn_batchnorm.ipynb ├── lab-11-0-cnn_basics.ipynb └── lab-12-0-rnn_basics.ipynb ├── keras ├── data-01-test-score.csv ├── data-02-stock_daily.csv ├── data-03-diabetes.csv ├── data-04-zoo.csv ├── klab-02-1-linear_regression.py ├── klab-04-1-multi_input_linear_regression.py ├── klab-04-2-multi_input_linear_regression.py ├── klab-04-3-file_input_linear_regression.py ├── klab-04-4-stock_linear_regression.py ├── klab-05-1-logistic_regression.py ├── klab-05-2-logistic_regression_diabetes.py ├── klab-06-1-softmax.py ├── klab-06-2-softmax_zoo.py ├── klab-07-1-learning_rate_and_evaluation.py ├── klab-07-2-linear_regression_without_min_max.py ├── klab-07-3-linear_regression_min_max.py ├── klab-07-4-mnist_introduction.py ├── klab-09-1-xor.py ├── klab-09-2-xor-nn.py ├── klab-10-1-mnist_softmax.py ├── klab-10-2-X1-mnist_conv_model_with_ensemble.py ├── klab-10-2-mnist_nn.py ├── klab-11-1-cnn_mnist.py ├── klab-11-X-cnn_cifar100_with_img_preprocess_and augumentation.py ├── klab-12-1-rnn_hello_char.py ├── klab-12-1-rnn_hello_char_acc1.0.py ├── klab-12-1-softmax_hello_char.py ├── klab-12-2-rnn_long_char.py ├── klab-12-3-rnn_stock_prediction.py ├── klab-12-4-rnn_deep_prediction.py ├── klab-12-5-seq2seq.py └── klab-13-2-mnist_tensorboard.py ├── lab-01-basics.ipynb ├── lab-02-1-linear_regression.py ├── lab-02-2-linear_regression_feed.py ├── lab-02-3-linear_regression_tensorflow.org.py ├── lab-03-1-minimizing_cost_show_graph.py ├── lab-03-2-minimizing_cost_gradient_update.py ├── lab-03-3-minimizing_cost_tf_optimizer.py ├── lab-03-X-minimizing_cost_tf_gradient.py ├── lab-04-1-multi_variable_linear_regression.py ├── lab-04-2-multi_variable_matmul_linear_regression.py ├── lab-04-3-file_input_linear_regression.py ├── lab-04-4-tf_reader_linear_regression.py ├── lab-05-1-logistic_regression.py ├── lab-05-2-logistic_regression_diabetes.py ├── lab-06-1-softmax_classifier.py ├── lab-06-2-softmax_zoo_classifier.py ├── lab-07-1-learning_rate_and_evaluation.py ├── lab-07-2-linear_regression_without_min_max.py ├── lab-07-3-linear_regression_min_max.py ├── lab-07-4-mnist_introduction.py ├── lab-08-tensor_manipulation.ipynb ├── lab-09-1-xor.py ├── lab-09-2-xor-nn.py ├── lab-09-3-xor-nn-wide-deep.py ├── lab-09-4-xor_tensorboard.py ├── lab-09-5-linear_back_prop.py ├── lab-09-6-multi-linear_back_prop.py ├── lab-09-7-sigmoid_back_prop.py ├── lab-09-x-xor-nn-back_prop.py ├── lab-10-1-mnist_softmax.py ├── lab-10-2-mnist_nn.py ├── lab-10-3-mnist_nn_xavier.py ├── lab-10-4-mnist_nn_deep.py ├── lab-10-5-mnist_nn_dropout.py ├── lab-10-6-mnist_nn_batchnorm.ipynb ├── lab-10-7-mnist_nn_higher_level_API.py ├── lab-10-8-mnist_nn_selu(wip).py ├── lab-10-X1-mnist_back_prop.py ├── lab-11-0-cnn_basics.ipynb ├── lab-11-1-mnist_cnn.py ├── lab-11-2-mnist_deep_cnn.py ├── lab-11-3-mnist_cnn_class.py ├── lab-11-4-mnist_cnn_layers.py ├── lab-11-5-mnist_cnn_ensemble_layers.py ├── lab-11-X-mnist_cnn_low_memory.py ├── lab-12-0-rnn_basics.ipynb ├── lab-12-1-hello-rnn.py ├── lab-12-2-char-seq-rnn.py ├── lab-12-3-char-seq-softmax-only.py ├── lab-12-4-rnn_long_char.py ├── lab-12-5-rnn_stock_prediction.py ├── lab-13-1-mnist_using_scope.py ├── lab-13-2-mnist_tensorboard.py ├── lab-13-3-mnist_save_restore.py ├── mxnet ├── README.md ├── data-01-test-score.csv ├── data-02-stock_daily.csv ├── data-03-diabetes.csv ├── data-04-zoo.csv ├── mxlab-04-3-file_input_linear_regression.py ├── mxlab-05-2-logistic_regression_diabetes.py ├── mxlab-06-2-softmax_zoo_classifier.py ├── mxlab-11-2-mnist_deep_cnn.py ├── mxlab-11-5-mnist_cnn_ensemble_layers.py ├── mxlab-12-4-rnn_deep_prediction.py └── mxlab-12-5-seq2seq.py ├── numpy ├── README.md ├── lab-05-1-logistic_regression.py └── lab-06-2-softmax_zoo_classifier.py ├── pytorch ├── data-01-test-score.csv ├── data-02-stock_daily.csv ├── data-03-diabetes.csv ├── data-04-zoo.csv ├── lab-02-1&2-linear_regression.py ├── lab-04-2-multi_variable_linear_regression.py ├── lab-04-3-file_input_linear_regression.py ├── lab-05-1-logistic_regression.py ├── lab-05-2-logistic_regression_diabetes.py ├── lab-06-1-softmax_classifier.py ├── lab-06-2-softmax_zoo_classifier.py ├── lab-09-1-xor.py ├── lab-09-2-xor-nn.py ├── lab-10-1-mnist_softmax.py ├── lab-10-2-mnist_nn.py ├── lab-10-3-mnist_nn_xavier.py ├── lab-10-4-mnist_nn_deep.py ├── lab-10-5-mnist_nn_dropout.py ├── lab-11-1-mnist_cnn.py ├── lab-11-2-mnist_deep_cnn.py ├── lab-11-3-mnist_cnn_class.py ├── lab-12-1-hello-rnn.py ├── lab-12-2-char-seq-rnn.py ├── lab-12-4-rnn-long_char.py └── lab-12-5-stock_prediction.py ├── requirements.txt ├── tests └── test_square.py └── tf2 ├── tf2-02-1-linear_regression.py ├── tf2-03-1-minimizing_cost_show_graph.py ├── tf2-04-1-multi_variable_linear_regression.py ├── tf2-04-3-file_input_linear_regression.py ├── tf2-05-1-logistic_regression.py ├── tf2-05-2-logistic_regression_diabetes.py ├── tf2-06-1-softmax_classifier.py ├── tf2-06-2-softmax_zoo_classifier.py ├── tf2-07-1-learning_rate_and_evaluation.py ├── tf2-07-2-linear_regression_without_min_max.py ├── tf2-07-3-linear_regression_min_max.py ├── tf2-09-1-xor.py ├── tf2-09-2-xor-nn.py ├── tf2-09-3-xor-nn-wide-deep.py ├── 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