In this post, we will learn all about Convolutional Neural Networks (CNN) in the context of an image classification problem. We first cover the basic structure of CNNs and then delve into the detailed ...
In this post, we’ll learn how to implement a Convolutional Neural Network (CNN) from scratch using Keras. Here, we show a CNN architecture similar to the structure of VGG-16 but with fewer layers. We ...
In this post, we cover the essential elements required for training Neural Networks for an image classification problem. We will still treat the internal network architecture as a black box so that we ...
Before studying deep neural networks, we will cover the fundamental components of a simple (linear) neural network. We'll begin with the topic of linear regression. Since linear regression can be ...
In this post, we will introduce several new concepts associated with the general problem of classification involving more than two classes. This is sometimes referred to as multinomial regression or ...
In this post, we’re going to provide a 30,000-Foot view of neural networks that’s aimed at absolute beginners who are looking to enter the field of Machine Learning and Deep Learning. In this ...
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In 2007, right after finishing my Ph.D., I co-founded TAAZ Inc. with my advisor Dr. David Kriegman and Kevin Barnes. The scalability, and robustness of our computer vision and machine learning algorithms have been put to rigorous test by more than 100M users who have tried our products.
