Digit Recognizer in Matlab using MNIST Dataset

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Digit Recognizer in Matlab using MNIST Dataset
.MP4 | Video: 1280x720, 30 fps(r) | Audio: AAC, 44100 Hz, 2ch | 623 MB
Duration: 1 hours | Genre: eLearning | Language: English

Machine Learning | Handwritten digit recognition with machine learning on the MNIST Dataset

What you'll learn

    A better understanding of MNIST dataset
    Can take part in various onine competitions involving MNIST Dataset
    Can also publish a research paper if you are able to achieve good results on testing
    Can train neural network on any type of dataset very easily in MATLAB

Requirements

    Working Matlab software with version 2015 or more.
    english language

Description

The problem of recognizing hand written characters is widely known. It holds a great potential and still research on it is being done to improve it further. Also it is one of the best problems to solve and understand using Neural Networks. The MNIST dataset is a benchmark dataset that is easily available and can be used to solve the problem in numerous ways. The problem holds a great potential and provide opportunities to learn the use of neural networks. In this course we will tackle the hand written character recognition problem using MNIST Data in Matlab. We will design a neural network model and test it on the test dataset. The good thing is that the same technique can be used to design a neural network for any other dataset and different problem.

Who this course is for:

    Anyone interested in designing Neural Network in MATLAB
    Anyone who wants to learn about working on MNIST Dataset
    Anyone interested in starting Machine Learning
       

               

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