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@@ -50,13 +50,6 @@ The following examples are coming from [TFLearn](https://github.com/tflearn/tfle
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- [Using HDF5](https://github.com/tflearn/tflearn/blob/master/examples/basics/use_hdf5.py). Use HDF5 to handle large datasets.
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- [Using DASK](https://github.com/tflearn/tflearn/blob/master/examples/basics/use_dask.py). Use DASK to handle large datasets.
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## Extending Tensorflow
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- [Layers](https://github.com/tflearn/tflearn/blob/master/examples/extending_tensorflow/layers.py). Use TFLearn layers along with Tensorflow.
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- [Trainer](https://github.com/tflearn/tflearn/blob/master/examples/extending_tensorflow/trainer.py). Use TFLearn trainer class to train any Tensorflow graph.
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- [Built-in Ops](https://github.com/tflearn/tflearn/blob/master/examples/extending_tensorflow/builtin_ops.py). Use TFLearn built-in operations along with Tensorflow.
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- [Summaries](https://github.com/tflearn/tflearn/blob/master/examples/extending_tensorflow/summaries.py). Use TFLearn summarizers along with Tensorflow.
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- [Variables](https://github.com/tflearn/tflearn/blob/master/examples/extending_tensorflow/variables.py). Use TFLearn variables along with Tensorflow.
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## Computer Vision
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- [Multi-layer perceptron](https://github.com/tflearn/tflearn/blob/master/examples/images/dnn.py). A multi-layer perceptron implementation for MNIST classification task.
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- [Convolutional Network (MNIST)](https://github.com/tflearn/tflearn/blob/master/examples/images/convnet_mnist.py). A Convolutional neural network implementation for classifying MNIST dataset.
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## Notebooks
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- [Spiral Classification Problem](https://github.com/tflearn/tflearn/blob/master/examples/notebooks/spiral.ipynb). TFLearn implementation of spiral classification problem from Stanford CS231n.
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## Extending Tensorflow
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- [Layers](https://github.com/tflearn/tflearn/blob/master/examples/extending_tensorflow/layers.py). Use TFLearn layers along with Tensorflow.
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- [Trainer](https://github.com/tflearn/tflearn/blob/master/examples/extending_tensorflow/trainer.py). Use TFLearn trainer class to train any Tensorflow graph.
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- [Built-in Ops](https://github.com/tflearn/tflearn/blob/master/examples/extending_tensorflow/builtin_ops.py). Use TFLearn built-in operations along with Tensorflow.
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- [Summaries](https://github.com/tflearn/tflearn/blob/master/examples/extending_tensorflow/summaries.py). Use TFLearn summarizers along with Tensorflow.
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- [Variables](https://github.com/tflearn/tflearn/blob/master/examples/extending_tensorflow/variables.py). Use TFLearn variables along with Tensorflow.
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## Dependencies
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```
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tensorflow

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