Arunangshu Das 
Introduction In the world of deep learning and computer vision, convolutional neural networks (CNNs) have played a transformative role. Among the most notable CNN architectures are VGG and LeNet-5, each representing a milestone in the evolution of deep learning. LeNet-5, introduced by Yann LeCun in 1998, marked the beginning of CNNs for digit recognition tasks, … Read more
Introduction to Regression in Deep Learning Regression is a fundamental concept in machine learning and deep learning, where the goal is to predict continuous values. From predicting house prices to forecasting stock trends, regression models serve as the backbone of many practical applications. Deep learning, with its ability to handle complex and high-dimensional data, takes … Read more
Introduction Deep learning has witnessed significant advancements over the decades, and LeNet-5 stands out as a foundational milestone. Developed by Yann LeCun and his collaborators in 1998, LeNet-5 was a revolutionary convolutional neural network (CNN) that demonstrated the power of convolutional architectures for tasks like handwritten digit recognition. Its contributions to the field of deep … Read more
Introduction to VGG Architecture In the ever-evolving field of deep learning, convolutional neural networks (CNNs) have proven indispensable for tasks like image recognition, object detection, and video analysis. Among the many groundbreaking architectures, the VGG network, introduced by the Visual Geometry Group at the University of Oxford in 2014, stands out as a milestone. VGG … Read more
Comparing VGG and LeNet-5 Architectures: Huge importance to solving complex problems such as image recognition, object detection, and many more are held by convolutional neural networks (CNNs) in the modern fast-developing directions of deep learning. From a vast family of CNN structures, LeNet-5 and VGG can be considered the most enshrine examples. All these differences … Read more