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<span id="tutorials"></span><h1>Tutorials<a class="headerlink" href="#tutorials" title="Permalink to this headline"></a></h1>
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<li class="toctree-l1"><a class="reference internal" href="datasets.html#appendix-upgrading-from-module-dataiter-to-gluon-dataloader">Appendix: Upgrading from Module <code class="docutils literal"><span class="pre">DataIter</span></code> to Gluon <code class="docutils literal"><span class="pre">DataLoader</span></code></a></li>
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<li class="toctree-l1"><a class="reference internal" href="gotchas_numpy_in_mxnet.html">Gotchas using NumPy in Apache MXNet</a><ul>
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<li class="toctree-l2"><a class="reference internal" href="gotchas_numpy_in_mxnet.html#converting-ndarray-to-numpy-array-blocks-calculation">Converting NDArray to NumPy Array blocks calculation</a></li>
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<li class="toctree-l3"><a class="reference internal" href="gotchas_numpy_in_mxnet.html#combine-a-higher-level-operator-using-a-few-lower-level-operators">Combine a higher level operator using a few lower level operators</a></li>
<li class="toctree-l3"><a class="reference internal" href="gotchas_numpy_in_mxnet.html#find-similar-operator-with-different-name-and-or-signature">Find similar operator with different name and/or signature</a></li>
<li class="toctree-l3"><a class="reference internal" href="gotchas_numpy_in_mxnet.html#search-for-an-operator-on-github">Search for an operator on Github</a></li>
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<li class="toctree-l2"><a class="reference internal" href="gotchas_numpy_in_mxnet.html#how-to-minimize-the-impact-of-blocking-calls">How to minimize the impact of blocking calls</a></li>
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<li class="toctree-l1"><a class="reference internal" href="info_gan.html">Image similarity search with InfoGAN</a><ul>
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<li class="toctree-l1"><a class="reference internal" href="learning_rate_finder.html">Learning Rate Finder</a><ul>
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<li class="toctree-l1"><a class="reference internal" href="learning_rate_schedules.html">Learning Rate Schedules</a><ul>
<li class="toctree-l2"><a class="reference internal" href="learning_rate_schedules.html#schedules">Schedules</a><ul>
<li class="toctree-l3"><a class="reference internal" href="learning_rate_schedules.html#stepwise-decay-schedule">Stepwise Decay Schedule</a></li>
<li class="toctree-l3"><a class="reference internal" href="learning_rate_schedules.html#polynomial-schedule">Polynomial Schedule</a></li>
<li class="toctree-l3"><a class="reference internal" href="learning_rate_schedules.html#custom-schedules">Custom Schedules</a></li>
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<li class="toctree-l2"><a class="reference internal" href="learning_rate_schedules.html#using-schedules">Using Schedules</a><ul>
<li class="toctree-l3"><a class="reference internal" href="learning_rate_schedules.html#manually-setting-the-learning-rate-gluon-api-only">Manually setting the learning rate: Gluon API only</a></li>
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<li class="toctree-l2"><a class="reference internal" href="learning_rate_schedules.html#advanced-schedules">Advanced Schedules</a></li>
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<li class="toctree-l1"><a class="reference internal" href="learning_rate_schedules_advanced.html">Advanced Learning Rate Schedules</a><ul>
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<li class="toctree-l3"><a class="reference internal" href="learning_rate_schedules_advanced.html#cosine">Cosine</a></li>
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<li class="toctree-l3"><a class="reference internal" href="learning_rate_schedules_advanced.html#cyclical">Cyclical</a></li>
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<li class="toctree-l1"><a class="reference internal" href="logistic_regression_explained.html">Logistic regression using Gluon API explained</a><ul>
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<li class="toctree-l2"><a class="reference internal" href="logistic_regression_explained.html#tip-1-use-only-one-neuron-in-the-output-layer">Tip 1: Use only one neuron in the output layer</a></li>
<li class="toctree-l2"><a class="reference internal" href="logistic_regression_explained.html#tip-2-encode-classes-as-0-and-1">Tip 2: Encode classes as 0 and 1</a></li>
<li class="toctree-l2"><a class="reference internal" href="logistic_regression_explained.html#tip-3-use-sigmoidbinarycrossentropyloss-instead-of-logisticregressionoutput">Tip 3: Use SigmoidBinaryCrossEntropyLoss instead of LogisticRegressionOutput</a></li>
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<li class="toctree-l1"><a class="reference internal" href="naming.html">Naming of Gluon Parameter and Blocks</a><ul>
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<li class="toctree-l1"><a class="reference internal" href="pretrained_models.html">Using pre-trained models in MXNet</a><ul>
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<li class="toctree-l3"><a class="reference internal" href="pretrained_models.html#densenet121">DenseNet121</a></li>
<li class="toctree-l3"><a class="reference internal" href="pretrained_models.html#mobilenet">MobileNet</a></li>
<li class="toctree-l3"><a class="reference internal" href="pretrained_models.html#resnet-18">Resnet-18</a></li>
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<li class="toctree-l2"><a class="reference internal" href="pretrained_models.html#fine-tuning-pre-trained-models">Fine-tuning pre-trained models</a><ul>
<li class="toctree-l3"><a class="reference external" href="http://gluon.mxnet.io/chapter08_computer-vision/fine-tuning.html">Transferring knowledge through fine-tuning</a></li>
<li class="toctree-l3"><a class="reference external" href="/versions/1.4.1/tutorials/onnx/fine_tuning_gluon.html">Fine Tuning an ONNX Model</a></li>
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<li class="toctree-l1"><a class="reference internal" href="save_load_params.html">Saving and Loading Gluon Models</a><ul>
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<li class="toctree-l2"><a class="reference internal" href="save_load_params.html#loading-model-parameters-from-file">Loading model parameters from file</a></li>
<li class="toctree-l2"><a class="reference internal" href="save_load_params.html#saving-model-parameters-and-architecture-to-file">Saving model parameters AND architecture to file</a></li>
<li class="toctree-l2"><a class="reference internal" href="save_load_params.html#loading-model-parameters-and-architecture-from-file">Loading model parameters AND architecture from file</a><ul>
<li class="toctree-l3"><a class="reference internal" href="save_load_params.html#from-a-different-frontend">From a different frontend</a><ul>
<li class="toctree-l4"><a class="reference external" href="https://github.com/apache/incubator-mxnet/blob/master/example/image-classification/predict-cpp/image-classification-predict.cc">Loading serialized Hybrid networks from C</a></li>
<li class="toctree-l4"><a class="reference external" href="https://github.com/apache/incubator-mxnet/blob/1.4.1/scala-package/infer/src/main/scala/org/apache/mxnet/infer/ImageClassifier.scala">Loading serialized Hybrid networks from Scala</a></li>
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<li class="toctree-l3"><a class="reference internal" href="save_load_params.html#from-python">From Python</a></li>
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