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Deep neural networks

Deep neural networks (DNNs) are a class of artificial neural networks (ANNs) that are deep in the sense that they have many layers of hidden units between the input and output layers. Deep neural networks are a type of deep learning, which is a type of machine learning. Deep neural networks are used in a variety of applications, including speech recognition, computer vision, and natural language processing. Deep neural networks are used in a variety of applications, including speech recognition, computer vision, and natural language processing.

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In this project, I used Python and TensorFlow to classify traffic signs. Dataset used: German Traffic Sign Dataset. This dataset has more than 50,000 images of 43 classes. I was able to reach a +99% validation accuracy, and a 97.3% testing accuracy.

  • Updated Dec 3, 2019
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We aim to generate realistic images from text descriptions using GAN architecture. The network that we have designed is used for image generation for two datasets: MSCOCO and CUBS.

  • Updated May 7, 2018
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Dog Breed classifier project of the Data Scientist Nanodegree by Udacity. A Web Application is developed using Flask through which a user can check if an uploaded image is that of a dog or human. Also, if the uploaded image is that of a human, the algorithm tells the user what dog breed the human resembles the most. The Deep Learning model disti…

  • Updated Nov 22, 2022
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This repository contains code and bonus content which will be added from time to time for the books "Learning Generative Adversarial Network- GAN" and "R Data Analysis Cookbook - 2nd Edition" by Packt

  • Updated Dec 27, 2021
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