Before going to Part 2 of the Famous Convolutional Neural Network Architectures series we need to go over some interesting variants of Convolution Operations! We will going over - Simple Convolutions, 1x1 Convs, Depth-Wise Separable Convolutions and Transposed Convolutions
We will build a simple model that will be able to take some details about a breast cancer and will inform us whether the cancer is Malignant (M) and Benign (B).
Let's go over some of the powerful Convolutional Neural Network which laid the foundation of today's Computer Vision achievements, achieved using Deep Learning - LeNet, AlexNet, VGGNet, GoogleNet and ResNet
In this post we will discuss about what is a python module, why is it necessary to have multiple modules rather than one and how packages come handy in dealing with a combination of modules. The post also describes how this approach helps us increase our efficiency in finding errors in code.
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