Classification of the MNIST dataset using various Deep Learning techniques
Deep Learning codes for MNIST with detailed explanation
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.
Trained a deep neural network architecture (CNN) on 60,000 images to classify 10 different images of clothing (FashionMNIST dataset).
A deep neural network with tensorflow and keras using mnist dataset
Code from Coursera Advanced Machine Learning specialization - Intro to Deep Learning - week 2.
Recognizing the Digits from 0-9 using their pixel values as attributes, using Deep Learning Model to Classify the Digits.
Batik motif classification (5 classes) using VGG16 transfer learning
Voted CNN for massive streaming EEG data classification
My solution to the Deep Learning Image Classification Assignment
Interactive Classification for Deep Learning Interpretation
This repository contains the project files and submissions for Project 2 - Image Classification as part of Udacity's Deep Learning Nanodegree Foundation Program.
Classifying videos based on a series of deep learning models.
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