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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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Learning Model Building in Scikit-learn : A Python Machine Learning Library

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A Beginners Guide to Neural Networks

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