Learn to build AlexNet from scratch with TensorFlow and R. Includes introduction to Tiny ImageNet, Rectified Linear Units (ReLU), convolutional neural networks and their relationship to receptive fields. You will learn how to translate the layers defined in the AlexNet paper to Keras layers and properly compile this model.
Resources:
- https://github.com/r-tensorflow/alexnet
- https://therinspark.com/extensions.html#deep-learning
- https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf
- https://tiny-imagenet.herokuapp.com/
- https://en.wikipedia.org/wiki/Rectifier_(neural_networks)
- https://cs231n.github.io/convolutional-networks/
- https://en.wikipedia.org/wiki/Receptive_field
