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  We encourage the use of the <a href="https://hypothes.is/">hypothes.is</a> extension to annote comments and discuss these notes inline.
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<div class="home">
  <div class="materials-wrap">
    
    <div class="module-header">Assignments</div>

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      <a href="assignment1/">
        Assignment #1: Image Classification, kNN, SVM, Softmax
      </a>
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      <a href="assignment2/">
        Assignment #2: Neural Networks, ConvNets I
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    <div class="materials-item">
      <a href="assignment3/">
        Assignment #3: ConvNets II, transfer learning, visualization
      </a>
    </div>

    <div class="module-header">Module 0: Preparation</div>

    <div class="materials-item">
      <a href="python-numpy-tutorial/">
        Python / Numpy tutorial
      </a>
    </div>

    <div class="materials-item">
      <a href="ipython-tutorial/">
        IPython notebook tutorial
      </a>
    </div>

    <div class="materials-item">
      <a href="terminal-tutorial/">
        Terminal.com tutorial
      </a>
    </div>
    
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    <div class="module-header">Module 1: Intro and Neural Networks</div>

    <div class="materials-item">
      <a href="classification/">
        Image classification: data-driven approach, nearest neighbor, train/val/test splits
      </a>
    </div>

    <div class="materials-item">
    <a href="linear-classify/">
         Linear classification: Support Vector Machine, Softmax
    </a>
    </div>

    <div class="materials-item">
    <a href="optimization-1/">
         Optimization: Stochastic Gradient Descent, gradient checks
    </a>
    </div>

    <div class="materials-item">
    <a href="optimization-2/">
         Backpropagation, intuitions
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    </div>

    <div class="materials-item">
    <a href="neural-networks/">
        Comprehensive reference to Neural Networks
    </a>
    </div>

    <div class="module-header">Module 2: Convolutional Neural Networks</div>

    <div class="materials-item">
    <a href="neuralnetwork2/">
      Convolutional Neural Networks: architectures, convolution / pooling layers    
    </a>
    </div>

    <div class="materials-item">
    <a href="neuralnetwork2/">
      Understanding and visualizing Convolutional Neural Networks
    </a>
    </div>

    <div class="materials-item">
    <a href="neuralnetwork2/">
      Transfer learning and fine-tuning Convolutional Neural Networks
    </a>
    </div>

    <div class="materials-item">
    <a href="neuralnetwork2/">
      ConvNet Tips and tricks: squeezing out the last few percent
    </a>
    </div>

    <div class="module-header">Module 3: CNN In the wild</div>

    <div class="materials-item">
    <a href="neuralnetwork2/">
      ImageNet challenge
    </a>
    </div>

    <div class="materials-item">
    <a href="neuralnetwork2/">
      Other visual recognition tasks: localization, detection
    </a>
    </div>

    <div class="materials-item">
    <a href="neuralnetwork2/">
      Beyond the ImageNet challenge
    </a>
    </div>

    <div class="materials-item">
    <a href="neuralnetwork2/">
      Convolutional Neural Networks in practice: Caffe
    </a>
    </div>


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