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LSTM and GRU Networks (Deep Learning Notes C5W1B)
introduction to LSTM and GRU networks: forward pass and backward pass
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Recurrent Neural Networks (Deep Learning Notes C5W1A)
basics of RNNs: features and problems; forward propagation and backward pass
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Neural Style Transfer (Deep Learning Notes C4W4)
generation of an image that blends the content from one image and the style of the other
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Face Recognition (Deep Learning Notes C4W4)
training a Siamese network for face recognition tasks with a triplet loss function
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Image Semantic Segmentation (Deep Learning Notes C4W3)
labelling and colouring the pixels of an image into a set of predefined classes
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Object Detection (Deep Learning Notes C4W3)
object detection and the YOLO algorithm
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Training Deeper CNNs (Deep Learning Notes C4W2)
residual networks (ResNets), depthwise separable convolutions and further advices
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Convolutional Neural Networks (Deep Learning Notes C4W1)
ABC of convolutional neural networks