Hi friends,
The Ultimate Guide to Convolutional Neural Networks is here!
CNNs are not easy to master, but our guide helps you understand their complexities and gain the clarity you need to apply this class of Deep Learning networks.
Here are the topics covered inside:
Convolution operation: explore feature detectors, feature maps, Rectified Linear Unit (ReLU) layer and dive into linearity functions in the context of CNNs
Pooling: explore various approaches to max pooling.
Flattening: how we move from pooled to flattened layers in CNNs.
Bonus tutorial covering Softmax and Cross-Entropy