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Variational Autoencoders in Machine Learning

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Understanding Variational Autoencoders Hey there! Have you ever heard of a special kind of computer wizard called a Variational Autoencoder (VAE)? Don't worry if it sounds like something out of a fantasy tale; I'll explain it to you in the simplest way possible, with easy-to-understand examples and some computer code sprinkled in where needed! Imagine you have a box of crayons, and your friend has to guess which colors you picked. Now, instead of telling your friend the exact colors, you give them hints. Maybe you say, "Most of them are shades of blue and green." Your friend then tries to guess the colors based on these hints. This is kind of like what a variational encoder does in ML. Introduction: The Enigma of VAEs In the vast landscape of machine learning, the Variational Autoencoder (VAE) shines as a beacon of innovation. But what exactly is a VAE? Imagine a magical entity capable of learning from images and then creating entirely new ones. This is the essence of...
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Flower detection & classification using CNN

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This machine learning project aims to create a flower recognition system that can identify the name of a flower from an input image. To achieve this, we will employ Convolutional Neural Networks (CNN), a powerful algorithm known for its exceptional performance in image-related tasks. By harnessing the capabilities of CNNs, we can efficiently process and extract meaningful features from images, thereby enabling precise flower recognition. So, let's build this model. Flower Recognition System The Flower Recognition System we will develop leverages the strengths of CNNs to automatically determine the name of a flower based on an input image. Such systems find extensive applications in various domains, including popular platforms like Google Lens, which enables users to identify flowers by simply pointing their smartphone cameras at them. By building our own flower recognition system, we not only gain insights into the inner workings of CNNs but also explore their practical application...
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A Beginners Guide to Neural Networks

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  “The neural network is this kind of technology that is not an algorithm, it is a network that has weights on it, and you can adjust the weights so that it learns. You teach it through trials.” — Howard Rheingold Ai is coming, AI is coming. That is all we hear these days and how it is going to severely impact everyone’s’ lives. Jobs will be lost, humans will be replaced by machines in every industry and many other dooming predictions that are written in magazines and blogs. How many people are even cognizant about what aspects of artificial intelligence there are out in the world?   This post is going to cover one of those such aspects, a beginner’s guide to neural networks. We will look at what neural networks are, how they operate, what are the different types and how they can and will impact our lives. Let’s begin by looking at what these networks are.                               ...
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