- These are the models studied, implemented and tested by me in the past;
- I used lightweight datasets, so even if you don't have GPU, you can still run these scripts;
- If you would like to support, please Star the project, many thanks!
- The following command clones all the files (>300MB);
git clone https://github.com/zhedongzheng/finch.git
- Use contents to find the model and test that may interest you, click on that test
- Find the test file path
- run on command line
cd finch/nlp-models/tensorflow
python rnn_attn_estimator_imdb_test.py
Py3 is perferred, but Py2 should also work in theory (if it doesn't please raise an issue)
Model
is implemented very early, usingfeed_dict
(most common but slowest data pipeline);- I am moving towards
Estimator
, which is based on tf.estimator.Estimator, more efficient;
- Python | LSA | Model for Visualization Test Result | Model for Concepts Test Result |
-
TensorFlow | CNN Model IMDB Test | Model (Multi-kernel) IMDB Test Result |
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TensorFlow | LSTM + Attention Model IMDB Test | Estimator IMDB Test IMDB Config |
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Python | 2nd order Markov Model Robert Frost Test |
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TensorFlow | Char-RNN Model | English Test Chinese Test | Model (Beam-Search) English Test |
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TensorFlow | BiLSTM Model | POS Tagging Test | Chinese Segmentation Test |
- TensorFlow | BiLSTM + CRF Model | POS Tagging Test | Chinese Segmentation Test |
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TensorFlow | Self-Attention Modules | POS Tagging Test |
- TensorFlow | Self-Attention + CRF Model | POS Tagging Test | Chinese Segmentation Test |
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TensorFlow | Seq2Seq Model Sorting Test | Estimator Sorting Test |
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TensorFlow | Seq2Seq + Attention Model Sorting Test |
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TensorFlow | Seq2Seq + BiLSTM Encoder Model Sorting Test |
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TensorFlow | Seq2Seq + Beam-Search Model Sorting Test |
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TensorFlow | Seq2Seq + BiLSTM Encoder + Attention + Beam-Search Model Sorting Test |
-
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TensorFlow | Attention Is All You Need |
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Python | Bayesian Inference Pixel Classification |
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TensorFlow | MLP Model MNIST Test CIFAR10 Test |
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TensorFlow | CNN Model MNIST Test CIFAR10 Test | Estimator MNIST Test |
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TensorFlow | RNN Model MNIST Test CIFAR10 Test | Estimator MNIST Test |
-
Autoencoder
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TensorFlow | Stacked Autoencoder (weights-tied) Model MNIST Test |
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TensorFlow | Denoising Autoencoder Model MNIST Test |
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TensorFlow | Sparse Autoencoder Model MNIST Test |
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TensorFlow | Variational Autoencoder Model MNIST Test |
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TensorFlow | Conv2D Autoencoder (weights-tied) Model MNIST Test CIFAR10 Test |
-
-
Generative Adversarial Network
- TensorFlow | DCGAN Model MNIST Test Result | Conditional Model MNIST Test |
-
OP | Resize
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OP | Rotations
-
Segmentation | Contours
-
Segmentation | Sorting Contours
-
Segmentation | Line detection
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Segmentation | Circle detection
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Segmentation | Blob detection
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Detection | Face & Eye Detection Using Cascade Classifier
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Detection | Walker & Car Detection Using Cascade Classifier
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Python | Apriori Model MovieLens Test |
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Python | Collborative Filtering | MovieLens User-based Model Test |
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TensorFlow | Matrix Factorization Model MovieLens Test |
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Python | Q-Learning Model CartPole Test |
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Python | Sarsa Model CartPole Test |
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TensorFlow | Policy Gradient Model CartPole Test |
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TensorFlow | K Nearest Neighbors Model MNIST Test |
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TensorFlow | K-Means Model MNIST Test |
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Python | Adaboost Pseudocode Model Test |
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TensorFlow | Random Forest Estimator & MNIST Test |
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TensorFlow | Gradient Boosting Trees Estimator & MNIST Test |