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<li class="toctree-l3"><a class="reference internal" href="r/charRnnModel.html">Char RNN Example</a></li> <li class="toctree-l3"><a class="reference internal" href="r/classifyRealImageWithPretrainedModel.html">Classify Images with a PreTrained Model</a></li> <li class="toctree-l3"><a class="reference internal" href="r/CustomIteratorTutorial.html">Custom Iterator Tutorial</a></li> <li class="toctree-l3"><a class="reference internal" href="r/CustomLossFunction.html">Custom Loss Function</a></li> <li class="toctree-l3"><a class="reference internal" href="r/fiveMinutesNeuralNetwork.html">Develop a Neural Network with MXNet in Five Minutes</a></li> <li class="toctree-l3"><a class="reference internal" href="r/mnistCompetition.html">Handwritten Digits Classification Competition</a></li> <li class="toctree-l3"><a class="reference internal" href="r/ndarray.html">NDArray: Vectorized Tensor Computations on CPUs and GPUs</a></li> <li class="toctree-l3"><a class="reference internal" href="r/symbol.html">Symbol and Automatic Differentiation</a></li> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="#Scala-Tutorials"><a>Scala</a><ul> <li class="toctree-l3"><a class="reference internal" href="scala/char_lstm.html">Char LSTM</a></li> <li class="toctree-l3"><a class="reference internal" href="scala/mnist.html">MNIST</a></li> <li class="toctree-l3"><a class="reference internal" href="scala/mxnet_scala_on_intellij.html">MXNet Scala on IntelliJ</a></li> </ul> </li> <li class="toctree-l2"><a class="reference internal" href="#contributing-tutorials">Contributing Tutorials</a></li> </ul> </li> </ul> </div> </div> <div class="content"> <div class="page-tracker"></div> <div class="section" id="tutorials"> <span id="tutorials"></span><h1>Tutorials<a class="headerlink" href="#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 <em>MXNet</em>. The <em>Basics</em> section contains tutorials on manipulating arrays, building networks, loading/preprocessing data, etc. The <em>Training and Inference</em> section talks about implementing Linear Regression, training a Handwritten digit classifier using MLP and CNN, running inferences using a pre-trained model, and lastly, efficiently training a large scale image classifier.</p> <p><strong>Note:</strong> We are working on a set of tutorials for the new imperative interface called Gluon. A preview version is hosted at <a class="reference external" href="https://gluon.mxnet.io">https://gluon.mxnet.io</a>.</p> <div class="section" id="python"> <span id="python"></span><h2>Python<a class="headerlink" href="#python" title="Permalink to this headline">¶</a></h2> <div class="section" id="basic"> <span id="basic"></span><h3>Basic<a class="headerlink" href="#basic" title="Permalink to this headline">¶</a></h3> <div class="toctree-wrapper compound"> <ul> <li class="toctree-l1"><a class="reference internal" href="basic/ndarray.html">NDArray - Imperative tensor operations on CPU/GPU</a></li> <li class="toctree-l1"><a class="reference internal" href="basic/symbol.html">Symbol - Neural network graphs and auto-differentiation</a></li> <li class="toctree-l1"><a class="reference internal" href="basic/module.html">Module - Neural network training and inference</a></li> <li class="toctree-l1"><a class="reference internal" href="basic/data.html">Iterators - Loading data</a></li> </ul> </div> </div> <div class="section" id="training-and-inference"> <span id="training-and-inference"></span><h3>Training and Inference<a class="headerlink" href="#training-and-inference" title="Permalink to this headline">¶</a></h3> <div class="toctree-wrapper compound"> <ul> <li class="toctree-l1"><a class="reference internal" href="python/linear-regression.html">Linear Regression</a></li> <li class="toctree-l1"><a class="reference internal" href="python/mnist.html">Handwritten Digit Recognition</a></li> <li class="toctree-l1"><a class="reference internal" href="python/predict_image.html">Predict with pre-trained models</a></li> <li class="toctree-l1"><a class="reference internal" href="vision/large_scale_classification.html">Large Scale Image Classification</a></li> </ul> </div> <p><br/> </div> <div class="section" id="embedded"> <span id="embedded"></span><h3>Embedded<a class="headerlink" href="#embedded" title="Permalink to this headline">¶</a></h3> <div class="toctree-wrapper compound"> <ul> <li class="toctree-l1"><a class="reference internal" href="embedded/wine_detector.html">Real-time Object Detection with MXNet On The Raspberry Pi</a></li> </ul> </div> <p><br/> </div> <div class="section" id="general-ml"> <span id="general-ml"></span><h3>General ML<a class="headerlink" href="#general-ml" title="Permalink to this headline">¶</a></h3> <div class="toctree-wrapper compound"> <ul> <li class="toctree-l1"><a class="reference internal" href="general_ml/recommendation_systems.html">Recommendation Systems</a></li> </ul> </div> <p><br/> </div> <div class="section" id="gluon"> <span id="gluon"></span><h3>Gluon<a class="headerlink" href="#gluon" title="Permalink to this headline">¶</a></h3> <div class="toctree-wrapper compound"> <ul> <li class="toctree-l1"><a class="reference internal" href="gluon/autograd.html">AutoGrad</a></li> <li class="toctree-l1"><a class="reference internal" href="gluon/customop.html">Custom Op</a></li> <li class="toctree-l1"><a class="reference internal" href="gluon/gluon.html">Gluon - Neural network building blocks</a></li> <li class="toctree-l1"><a class="reference internal" href="gluon/hybrid.html">Hybrid</a></li> <li class="toctree-l1"><a class="reference internal" href="gluon/mnist.html">MNIST</a></li> <li class="toctree-l1"><a class="reference internal" href="gluon/ndarray.html">NDArray</a></li> </ul> </div> <p><br/> </div> <div class="section" id="nlp"> <span id="nlp"></span><h3>NLP<a class="headerlink" href="#nlp" title="Permalink to this headline">¶</a></h3> <div class="toctree-wrapper compound"> <ul> <li class="toctree-l1"><a class="reference internal" href="nlp/cnn.html">CNN</a></li> <li class="toctree-l1"><a class="reference internal" href="nlp/nce_loss.html">NCE Loss</a></li> <li class="toctree-l1"><a class="reference internal" href="nlp/rnn.html">RNN</a></li> </ul> </div> <p><br/> </div> <div class="section" id="speech-recognition"> <span id="speech-recognition"></span><h3>Speech Recognition<a class="headerlink" href="#speech-recognition" title="Permalink to this headline">¶</a></h3> <div class="toctree-wrapper compound"> <ul> <li class="toctree-l1"><a class="reference internal" href="speech_recognition/baidu_warp_ctc.html">Baidu Warp CTC</a></li> <li class="toctree-l1"><a class="reference internal" href="speech_recognition/speech_lstm.html">Speech LSTM</a></li> </ul> </div> <p><br/> </div> <div class="section" id="unsupervised-learning"> <span id="unsupervised-learning"></span><h3>Unsupervised Learning<a class="headerlink" href="#unsupervised-learning" title="Permalink to this headline">¶</a></h3> <div class="toctree-wrapper compound"> <ul> <li class="toctree-l1"><a class="reference internal" href="unsupervised_learning/auto_encoders.html">AutoEncoders</a></li> <li class="toctree-l1"><a class="reference internal" href="unsupervised_learning/gan.html">Generative Adversarial Networks (GANs)</a></li> </ul> </div> <p><br/> </div> </div> <div class="section" id="cpp"> <span id="cpp"></span><h2>C++<a class="headerlink" href="#C-Tutorials" title="Permalink to this headline">¶</a></h2> <div class="toctree-wrapper compound"> <ul> <li class="toctree-l1"><a class="reference internal" href="c++/basics.html">Basics</a></li> </ul> </div> <p><br/> </div> <div class="section" id="r"> <span id="r"></span><h2>R<a class="headerlink" href="#R-Tutorials" title="Permalink to this headline">¶</a></h2> <div class="toctree-wrapper compound"> <ul> <li class="toctree-l1"><a class="reference internal" href="r/CallbackFunctionTutorial.html">Callback Function</a></li> <li class="toctree-l1"><a class="reference internal" href="r/charRnnModel.html">Char RNN Example</a></li> <li class="toctree-l1"><a class="reference internal" href="r/classifyRealImageWithPretrainedModel.html">Classify Images with a PreTrained Model</a></li> <li class="toctree-l1"><a class="reference internal" href="r/CustomIteratorTutorial.html">Custom Iterator Tutorial</a></li> <li class="toctree-l1"><a class="reference internal" href="r/CustomLossFunction.html">Custom Loss Function</a></li> <li class="toctree-l1"><a class="reference internal" href="r/fiveMinutesNeuralNetwork.html">Develop a Neural Network with MXNet in Five Minutes</a></li> <li class="toctree-l1"><a class="reference internal" href="r/mnistCompetition.html">Handwritten Digits Classification Competition</a></li> <li class="toctree-l1"><a class="reference internal" href="r/ndarray.html">NDArray: Vectorized Tensor Computations on CPUs and GPUs</a></li> <li class="toctree-l1"><a class="reference internal" href="r/symbol.html">Symbol and Automatic Differentiation</a></li> </ul> </div> <p><br/> </div> <div class="section" id="scala"> <span id="scala"></span><h2>Scala<a class="headerlink" href="#Scala-Tutorials" title="Permalink to this headline">¶</a></h2> <div class="toctree-wrapper compound"> <ul> <li class="toctree-l1"><a class="reference internal" href="scala/char_lstm.html">Char LSTM</a></li> <li class="toctree-l1"><a class="reference internal" href="scala/mnist.html">MNIST</a></li> <li class="toctree-l1"><a class="reference internal" href="scala/mxnet_scala_on_intellij.html">MXNet Scala on IntelliJ</a></li> </ul> </div> <p><br/> More tutorials and examples are available in the GitHub <a class="reference external" href="https://github.com/apache/incubator-mxnet/tree/v0.11.0/example">repository</a>.</p> </div> <div class="section" id="contributing-tutorials"> <span id="contributing-tutorials"></span><h2>Contributing Tutorials<a class="headerlink" href="#contributing-tutorials" title="Permalink to this headline">¶</a></h2> <p>Want to contribute an MXNet tutorial? To get started, download the <a class="reference external" href="https://github.com/dmlc/mxnet/tree/master/example/MXNetTutorialTemplate.ipynb">tutorial template</a>.</p> </div> </div> </div> </div> <div aria-label="main navigation" class="sphinxsidebar rightsidebar" role="navigation"> <div class="sphinxsidebarwrapper"> <h3><a href="../index.html">Table Of Contents</a></h3> <ul> <li><a class="reference internal" href="#">Tutorials</a><ul> <li><a class="reference internal" href="#python">Python</a><ul> <li><a class="reference internal" href="#basic">Basic</a></li> <li><a class="reference internal" href="#training-and-inference">Training and Inference</a></li> </ul> </li> <li><a class="reference internal" href="#contributing-tutorials">Contributing Tutorials</a></li> </ul> </li> </ul> </div> </div> </div><div class="footer"> <div class="section-disclaimer"> <div class="container"> <div> <img height="60" src="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/image/apache_incubator_logo.png"/> <p> Apache MXNet is an effort undergoing incubation at The Apache Software Foundation (ASF), <strong>sponsored by the <i>Apache Incubator</i></strong>. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF. </p> <p> "Copyright © 2017-2018, The Apache Software Foundation Apache MXNet, MXNet, Apache, the Apache feather, and the Apache MXNet project logo are either registered trademarks or trademarks of the Apache Software Foundation." </p> </div> </div> </div> </div>  </div> <script crossorigin="anonymous" integrity="sha384-0mSbJDEHialfmuBBQP6A4Qrprq5OVfW37PRR3j5ELqxss1yVqOtnepnHVP9aJ7xS" src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.6/js/bootstrap.min.js"></script> <script src="../_static/js/sidebar.js" type="text/javascript"></script> <script src="../_static/js/search.js" type="text/javascript"></script> <script src="../_static/js/navbar.js" type="text/javascript"></script> <script src="../_static/js/clipboard.min.js" type="text/javascript"></script> <script src="../_static/js/copycode.js" type="text/javascript"></script> <script src="../_static/js/page.js" type="text/javascript"></script> <script src="../_static/js/docversion.js" type="text/javascript"></script> <script type="text/javascript"> $('body').ready(function () { $('body').css('visibility', 'visible'); }); </script> </body> </html>

versions/0.11.0/tutorials/index.html (441 lines of code) (raw):