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Updated to TensorFlow 1.9
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‎01_Simple_Linear_Model.ipynb

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‎02_Convolutional_Neural_Network.ipynb

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‎03B_Layers_API.ipynb

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‎03C_Keras_API.ipynb

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‎03_PrettyTensor.ipynb

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‎04_Save_Restore.ipynb

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"/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)"
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## WARNING!\n",
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"\n",
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"**This tutorial does not work with TensorFlow v. 1.9 due to the PrettyTensor builder API apparently no longer being updated and supported by the Google Developers. It is recommended that you use the _Keras API_ instead, which also makes it much easier to save and load a model, see Tutorial #03-C.**"
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},
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"cell_type": "markdown",
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"metadata": {},
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"collapsed": false,
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"outputs": [
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"metadata": {},
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"data": {
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [],
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"source": [
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"data.test.cls = np.argmax(data.test.labels, axis=1)\n",
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"cell_type": "code",
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"data": {
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"metadata": {},
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"weights_conv1 = get_weights_variable(layer_name='layer_conv1')\n",
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"execution_count": 19,
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"metadata": {},
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"optimizer = tf.train.AdamOptimizer(learning_rate=1e-4).minimize(loss)"
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"cell_type": "code",
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"metadata": {},
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"outputs": [],
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"save_path = os.path.join(save_dir, 'best_validation')"
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"metadata": {},
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"init_variables()"
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"metadata": {},
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"# Counter for total number of iterations performed so far.\n",
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"def print_test_accuracy(show_example_errors=False,\n",
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"init_variables()"
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"# This has been commented out in case you want to modify and experiment\n",
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"metadata": {
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"anaconda-cloud": {},
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"kernelspec": {
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"display_name": "Python [conda env:tf-gpu]",
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"display_name": "Python 3",
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"language": "python",
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"name": "conda-env-tf-gpu-py"
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"name": "python3"
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"language_info": {
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"codemirror_mode": {
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.5.2"
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"version": "3.6.1"
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"nbformat": 4,
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