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| BUILD | D | 03-May-2024 | 3.4 KiB | 167 | 147 | |
| README.md | D | 03-May-2024 | 2.1 KiB | 35 | 24 | |
| boston.py | D | 03-May-2024 | 2.5 KiB | 72 | 36 | |
| examples_test.sh | D | 03-May-2024 | 1.5 KiB | 59 | 34 | |
| hdf5_classification.py | D | 03-May-2024 | 2.8 KiB | 82 | 45 | |
| iris.py | D | 03-May-2024 | 3.9 KiB | 117 | 66 | |
| iris_custom_decay_dnn.py | D | 03-May-2024 | 3.5 KiB | 101 | 57 | |
| iris_custom_model.py | D | 03-May-2024 | 3.4 KiB | 98 | 54 | |
| iris_run_config.py | D | 03-May-2024 | 2.5 KiB | 72 | 35 | |
| mnist.py | D | 03-May-2024 | 4.6 KiB | 134 | 83 | |
| multiple_gpu.py | D | 03-May-2024 | 3.9 KiB | 117 | 68 | |
| random_forest_mnist.py | D | 03-May-2024 | 4 KiB | 138 | 105 | |
| resnet.py | D | 03-May-2024 | 6.2 KiB | 201 | 130 | |
| text_classification.py | D | 03-May-2024 | 6.4 KiB | 181 | 111 | |
| text_classification_character_cnn.py | D | 03-May-2024 | 5.3 KiB | 161 | 110 | |
| text_classification_character_rnn.py | D | 03-May-2024 | 3.9 KiB | 123 | 81 | |
| text_classification_cnn.py | D | 03-May-2024 | 5.1 KiB | 154 | 104 |
README.md
1# Estimator Examples 2 3TensorFlow Estimators are a high-level API for TensorFlow that allows you to 4create, train, and use deep learning models easily. 5 6See the [Quickstart tutorial](https://www.tensorflow.org/get_started/estimator) 7for an introduction to the API. 8 9To run most of these examples, you need to install the `scikit learn` library 10(`pip install -U scikit-learn`). Some examples use the `pandas` library for data 11processing (`pip install -U pandas`). 12 13## Basics 14 15* [Deep Neural Network Regression with Boston Data](https://www.tensorflow.org/code/tensorflow/examples/learn/boston.py) 16* [Deep Neural Network Classification with Iris Data](https://www.tensorflow.org/code/tensorflow/examples/learn/iris.py) 17* [Building a Custom Model](https://www.tensorflow.org/code/tensorflow/examples/learn/iris_custom_model.py) 18* [Building a Model Using Different GPU Configurations](https://www.tensorflow.org/code/tensorflow/examples/learn/iris_run_config.py) 19 20## Techniques 21 22* [Deep Neural Network with Customized Decay Function](https://www.tensorflow.org/code/tensorflow/examples/learn/iris_custom_decay_dnn.py) 23 24## Specialized Models 25* [Building a Random Forest Model](https://www.tensorflow.org/code/tensorflow/examples/learn/random_forest_mnist.py) 26* [Building a Wide & Deep Model](https://github.com/tensorflow/models/tree/master/official/wide_deep/wide_deep.py) 27* [Building a Residual Network Model](https://www.tensorflow.org/code/tensorflow/examples/learn/resnet.py) 28 29## Text classification 30 31* [Text Classification Using Recurrent Neural Networks on Words](https://www.tensorflow.org/code/tensorflow/examples/learn/text_classification.py) 32* [Text Classification Using Convolutional Neural Networks on Words](https://www.tensorflow.org/code/tensorflow/examples/learn/text_classification_cnn.py) 33* [Text Classification Using Recurrent Neural Networks on Characters](https://www.tensorflow.org/code/tensorflow/examples/learn/text_classification_character_rnn.py) 34* [Text Classification Using Convolutional Neural Networks on Characters](https://www.tensorflow.org/code/tensorflow/examples/learn/text_classification_character_cnn.py) 35