Stride and Calculation of Output Size
[latexpage] In the last lesson, we discussed shifting the convolution filter (kernel) by one pixel at a time, i.e., by …
[latexpage] In the last lesson, we discussed shifting the convolution filter (kernel) by one pixel at a time, i.e., by …
[latexpage] The convolution operation is the fundamental algorithmic backbone of a Convolutional Neural Network (CNN). The convolution operation takes in …
Convolutional Neural Network (CNN) is a type of neural network Architecture that is widely used for performing deep learning on …
Welcome to this course on Convolutional Neural Networks! In this course, you will be learning the theoretical concepts behind building …
[latexpage] The learning process of a deep neural network is also very similar to the learning process of a neuron. …
[latexpage] A deep neural network is an interconnection of neurons collectively working together. It is made up of three different …
[latexpage] Before we get started on discussing how a neuron learns, let us first understand how a human learns to …
[latexpage] In the last lesson, we left out talking about activation functions since they required a lesson of their own. …
[latexpage] Neurons in Deep Learning are computational units that take in real-valued inputs of features, processes them, and produces real-valued …
In the last course, we built up a solid theoretical as well as a practical foundation on Machine Learning in …