giakou4/MNIST_classification
Classification of the MNIST dataset using various Deep Learning techniques

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Classification of the MNIST dataset using various Deep Learning techniques

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Deep Learning codes for MNIST with detailed explanation

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There's been much speculation in recent years about neural networks technologies and other deep learning algorithms, primarily because of the popularity of several implementations in the sector utilizing these techniques. Consequently, this hype has yielded several innovative ideas to build open-source libraries and methods to enable the average income tech-savvies to achieve their objective. This research paper aims to examine and illustrate how to use deep learning technologies and algorithms to precisely classify a dataset of fashion images into their respective clothing categories. First, the paper shows the general knowledge of convolutional neural networks (CNN) and the techniques of image classification. Later on, it also discusses the methodology of building a neural network and the simulation process. The results of the neural network simulation are compressively evaluated and discussed.

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Trained a deep neural network architecture (CNN) on 60,000 images to classify 10 different images of clothing (FashionMNIST dataset).

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A deep neural network with tensorflow and keras using mnist dataset

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(no description)

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Code from Coursera Advanced Machine Learning specialization - Intro to Deep Learning - week 2.

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MNIST-Dataset πŸ‚

Recognizing the Digits from 0-9 using their pixel values as attributes, using Deep Learning Model to Classify the Digits.

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Batik motif classification (5 classes) using VGG16 transfer learning

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Voted CNN for massive streaming EEG data classification

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My solution to the Deep Learning Image Classification Assignment

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Interactive Classification for Deep Learning Interpretation

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This repository contains the project files and submissions for Project 2 - Image Classification as part of Udacity's Deep Learning Nanodegree Foundation Program.

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Classifying videos based on a series of deep learning models.

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Various State of the Art Deep Learning models for Text Classification inspired by different tasks in NLP

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