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Classifying images from the [CIFAR-10 dataset](https://www.cs.toronto.edu/~kriz/cifar.html). The dataset consists of airplanes, dogs, cats, and other objects. Preprocess of the images, then training a convolutional neural network on all the samples. The images are normalized and the labels are one-hot encoded. You'll get to see the convolutional, max pooling, dropout, and fully connected layers. At the end, you'll get to see the neural network's predictions on the sample images.

License: GNU General Public License v3.0

Python 2.25% HTML 74.89% Jupyter Notebook 22.86%
convolutional-neural-networks machine-learning tensorflow

cnn-image-classifier's Introduction

The Engineer's Plan

Hi, I am Ravin ๐Ÿ‘‹

A curious person ๐Ÿ™‚ blessed ๐Ÿ˜‡ to see life as an artist ๐ŸŽจ, engineer ๐ŸŽ“, researcher ๐Ÿค–, inventor โš™๏ธ, economist ๐Ÿ“ˆ, poet ๐Ÿ–‹๏ธ, mathematician ๐ŸŽฒ, hacker ๐Ÿ‘พ, game developer ๐ŸŽฎ, writer โœ๏ธ...

Some of his achievements are mentioned below:

๐Ÿคฉ Excited to know more, do visit his personal website: RAVIN KUMAR

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