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In this project i have applied deep learning techniques to train a model to classify images using convolutional neural network algorithm.

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Rajat-dhyani/ImageNetBot

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Image Net Bot

Udacity - Machine learning Nano Degree Program : Project-5

Project Overview

This is fifth project in the series of the projects listed in Udacity- Machine Learning Nano Degree Program.

In this project, I have classified images from the CIFAR-10 dataset. The dataset consists of airplanes, dogs, cats, and other objects. The dataset was first preprocessed, then trained a convolutional neural network on all the samples. I have normalized the images, one-hot encoded the labels, build a convolutional layer, max pool layer, and fully connected layer.

Image-Net-Bot

Project Highlights

In this project i have applied deep learning techniques to train a model to classify images using convolutional neural network algorithm. I have also learnt how to apply my knowledge of neural networks on real datasets using TensorFlow, an open source Deep Learning library created by Google.

Achievements:

  • Built an image classification bot using convolutional neural networks to classify images from the CIFAR-10 dataset.
  • Achieved accuracy of 60.42 %.

Things i have learnt by completing this project:

  • How to apply deep learning techniques: Convolutional Neural Network algorithms.
  • How to use tensorflow library.
  • How to preprocess given data.
  • How to analyze model's performance.
  • How to optimise Convolutional Neural Network algortithm, to ensure increase in postive results.

Other Related Projects:

Software and Libraries

This project uses the following software and Python libraries:

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In this project i have applied deep learning techniques to train a model to classify images using convolutional neural network algorithm.

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