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<span id="r-tutorials"></span><h1>R Tutorials<a class="headerlink" href="#r-tutorials" title="Permalink to this headline"></a></h1>
<p>These tutorials introduce a few fundamental concepts in deep learning and how to implement them in R using <em>MXNet</em>.</p>
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<li class="toctree-l1"><a class="reference internal" href="CallbackFunction.html">Callback Function</a><ul>
<li class="toctree-l2"><a class="reference internal" href="CallbackFunction.html#model-training-example">Model Training Example</a></li>
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<li class="toctree-l2"><a class="reference internal" href="CallbackFunction.html#how-to-write-your-own-callback-functions">How to Write Your Own Callback Functions</a></li>
<li class="toctree-l2"><a class="reference internal" href="CallbackFunction.html#next-steps">Next Steps</a><ul>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/fiveMinutesNeuralNetwork.html">Neural Networks with MXNet in Five Minutes</a></li>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/classifyRealImageWithPretrainedModel.html">Classify Real-World Images with a Pretrained Model</a></li>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/mnistCompetition.html">Handwritten Digits Classification Competition</a></li>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/charRnnModel.html">Character Language Model Using RNN</a></li>
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<li class="toctree-l1"><a class="reference internal" href="CustomIterator.html">Custom Iterator Tutorial</a><ul>
<li class="toctree-l2"><a class="reference internal" href="CustomIterator.html#getting-the-data">Getting the data</a></li>
<li class="toctree-l2"><a class="reference internal" href="CustomIterator.html#custom-csv-iterator">Custom CSV Iterator</a></li>
<li class="toctree-l2"><a class="reference internal" href="CustomIterator.html#cnn-model">CNN Model</a></li>
<li class="toctree-l2"><a class="reference internal" href="CustomIterator.html#training-with-the-custom-iterator">Training with the Custom Iterator</a></li>
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<li class="toctree-l2"><a class="reference internal" href="CustomLossFunction.html#model-training-example">Model Training Example</a></li>
<li class="toctree-l2"><a class="reference internal" href="CustomLossFunction.html#how-to-use-your-own-loss-function">How to Use Your Own Loss Function</a></li>
<li class="toctree-l2"><a class="reference internal" href="CustomLossFunction.html#next-steps">Next Steps</a><ul>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/fiveMinutesNeuralNetwork.html">Neural Networks with MXNet in Five Minutes</a></li>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/classifyRealImageWithPretrainedModel.html">Classify Real-World Images with a PreTrained Model</a></li>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/mnistCompetition.html">Handwritten Digits Classification Competition</a></li>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/charRnnModel.html">Character Language Model Using RNN</a></li>
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<li class="toctree-l1"><a class="reference internal" href="MultidimLstm.html">LSTM time series example</a><ul>
<li class="toctree-l2"><a class="reference internal" href="MultidimLstm.html#load-and-pre-process-the-data">Load and pre-process the data</a></li>
<li class="toctree-l2"><a class="reference internal" href="MultidimLstm.html#defining-and-training-the-network">Defining and training the network</a></li>
<li class="toctree-l2"><a class="reference internal" href="MultidimLstm.html#inference-on-the-network">Inference on the network</a></li>
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<li class="toctree-l1"><a class="reference internal" href="charRnnModel.html">Character-level Language Model using RNN</a><ul>
<li class="toctree-l2"><a class="reference internal" href="charRnnModel.html#preprocess-and-prepare-the-data">Preprocess and prepare the data</a></li>
<li class="toctree-l2"><a class="reference internal" href="charRnnModel.html#train-the-model">Train the Model</a></li>
<li class="toctree-l2"><a class="reference internal" href="charRnnModel.html#inference-on-the-model">Inference on the Model</a></li>
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<li class="toctree-l1"><a class="reference internal" href="classifyRealImageWithPretrainedModel.html">Classify Images with a PreTrained Model</a><ul>
<li class="toctree-l2"><a class="reference internal" href="classifyRealImageWithPretrainedModel.html#load-the-mxnet-package">Load the MXNet Package</a></li>
<li class="toctree-l2"><a class="reference internal" href="classifyRealImageWithPretrainedModel.html#load-the-pretrained-model">Load the PreTrained Model</a></li>
<li class="toctree-l2"><a class="reference internal" href="classifyRealImageWithPretrainedModel.html#load-and-preprocess-the-image">Load and Preprocess the Image</a></li>
<li class="toctree-l2"><a class="reference internal" href="classifyRealImageWithPretrainedModel.html#classify-the-image">Classify the Image</a></li>
<li class="toctree-l2"><a class="reference internal" href="classifyRealImageWithPretrainedModel.html#reference">Reference</a></li>
<li class="toctree-l2"><a class="reference internal" href="classifyRealImageWithPretrainedModel.html#next-steps">Next Steps</a><ul>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/mnistCompetition.html">Handwritten Digits Classification Competition</a></li>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/charRnnModel.html">Character Language Model using RNN</a></li>
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<li class="toctree-l1"><a class="reference internal" href="fiveMinutesNeuralNetwork.html">Develop a Neural Network with MXNet in Five Minutes</a><ul>
<li class="toctree-l2"><a class="reference internal" href="fiveMinutesNeuralNetwork.html#classification">Classification</a></li>
<li class="toctree-l2"><a class="reference internal" href="fiveMinutesNeuralNetwork.html#regression">Regression</a></li>
<li class="toctree-l2"><a class="reference internal" href="fiveMinutesNeuralNetwork.html#next-steps">Next Steps</a><ul>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/classifyRealImageWithPretrainedModel.html">Classify Real-World Images with Pre-trained Model</a></li>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/mnistCompetition.html">Handwritten Digits Classification Competition</a></li>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/charRnnModel.html">Character Language Model using RNN</a></li>
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<li class="toctree-l1"><a class="reference internal" href="mnistCompetition.html">Handwritten Digits Classification Competition</a><ul>
<li class="toctree-l2"><a class="reference internal" href="mnistCompetition.html#loading-the-data">Loading the Data</a></li>
<li class="toctree-l2"><a class="reference internal" href="mnistCompetition.html#configuring-the-network">Configuring the Network</a></li>
<li class="toctree-l2"><a class="reference internal" href="mnistCompetition.html#training">Training</a></li>
<li class="toctree-l2"><a class="reference internal" href="mnistCompetition.html#making-a-prediction-and-submitting-to-the-competition">Making a Prediction and Submitting to the Competition</a></li>
<li class="toctree-l2"><a class="reference internal" href="mnistCompetition.html#lenet">LeNet</a></li>
<li class="toctree-l2"><a class="reference internal" href="mnistCompetition.html#next-steps">Next Steps</a><ul>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/charRnnModel.html">Character Language Model using RNN</a></li>
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<li class="toctree-l1"><a class="reference internal" href="ndarray.html">NDArray: Vectorized Tensor Computations on CPUs and GPUs</a><ul>
<li class="toctree-l2"><a class="reference internal" href="ndarray.html#create-and-initialize">Create and Initialize</a></li>
<li class="toctree-l2"><a class="reference internal" href="ndarray.html#performing-basic-operations">Performing Basic Operations</a><ul>
<li class="toctree-l3"><a class="reference internal" href="ndarray.html#elemental-wise-operations">Elemental-wise Operations</a></li>
<li class="toctree-l3"><a class="reference internal" href="ndarray.html#loading-and-saving">Loading and Saving</a></li>
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<li class="toctree-l2"><a class="reference internal" href="ndarray.html#automatic-parallelization">Automatic Parallelization</a></li>
<li class="toctree-l2"><a class="reference internal" href="ndarray.html#next-steps">Next Steps</a><ul>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/symbol.html">Symbol</a></li>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/CallbackFunction.html">Write and use callback functions</a></li>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/fiveMinutesNeuralNetwork.html">Neural Networks with MXNet in Five Minutes</a></li>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/classifyRealImageWithPretrainedModel.html">Classify Real-World Images with Pre-trained Model</a></li>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/mnistCompetition.html">Handwritten Digits Classification Competition</a></li>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/charRnnModel.html">Character Language Model using RNN</a></li>
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<li class="toctree-l1"><a class="reference internal" href="symbol.html">Symbol and Automatic Differentiation</a><ul>
<li class="toctree-l2"><a class="reference internal" href="symbol.html#basic-composition-of-symbols">Basic Composition of Symbols</a></li>
<li class="toctree-l2"><a class="reference internal" href="symbol.html#more-complicated-composition-of-symbols">More Complicated Composition of Symbols</a></li>
<li class="toctree-l2"><a class="reference internal" href="symbol.html#training-a-neural-net">Training a Neural Net</a></li>
<li class="toctree-l2"><a class="reference internal" href="symbol.html#how-efficient-is-the-symbolic-api">How Efficient Is the Symbolic API?</a></li>
<li class="toctree-l2"><a class="reference internal" href="symbol.html#next-steps">Next Steps</a><ul>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/CallbackFunction.html">Write and use callback functions</a></li>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/fiveMinutesNeuralNetwork.html">Neural Networks with MXNet in Five Minutes</a></li>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/classifyRealImageWithPretrainedModel.html">Classify Real-World Images with Pre-trained Model</a></li>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/mnistCompetition.html">Handwritten Digits Classification Competition</a></li>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/r/charRnnModel.html">Character Language Model using RNN</a></li>
</ul>
</li>
</ul>
</li>
</ul>
</div>
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<p>More tutorials and examples are available in the GitHub <a class="reference external" href="https://github.com/apache/incubator-mxnet/tree/master/example">repository</a>.</p>
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