The Amazing World of AI

  What is an autoencoder? Autoencoders are  neural networks that you can use to compress and reconstruct data . An autoencoder is a type of artificial neural network that takes some kind of input data which can be images, vectors, audio or whatever, and it first compresses the original input data into a lower dimension and then uses this lower dimensional representation of the data to recreate the original input! Autoencoder model architecture An autoencoder consists of three major components as illustrated above: An encoder which is a module that compresses the input data into an encoded representation that is several times smaller than the input data The Bottleneck or Code which contains the compressed representations And the decoder module that decompresses the bottleneck representation and tries to reconstruct the data back from its encoded form. Applications of autoencoder models Anomaly Detection Anomaly detection is a perfect example, where we train the model on normal ...

  Introduction: In today's rapidly advancing world of technology, there's no doubt that artificial intelligence (AI) is at the forefront of innovation. Among the many exciting developments in AI ,  Convolutional Neural Networks   (CNNs) stand out as a key player in transforming how computers understand and interact with visual data. This Blog is your guide to understanding CNNs What Are Convolutional Neural Networks (CNNs)? Convolutional Neural Networks, or CNNs, are a type of artificial neural network specially designed to process and analyze visual data like images and videos. Inspired by the human visual system, CNNs excel at recognizing patterns, shapes, and objects in images, much like how our own brains do. They have become the backbone of many technological advancements in computer vision Breaking Down the Concept: CNN works through a series of stages, each contributing to the network's ability to understand images: 1. Convolution: Think of this like looking at a p...