Image classification using CNN (CIFAR10 dataset) | Deep Learning Tutorial 24 (Tensorflow & Python)

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In this video we will do small image classification using CIFAR10 dataset in tensorflow. We will use convolutional neural network for this image classification problem. First we will train a model using simple artificial neural network and then check how the performance looks like and then we will train a CNN and see how the model accuracy improves. This tutorial will help you understand why CNN is preferred over ANN for image classification.

Exercise: Scroll to the very end of above notebook. You will find exercise description and solution link

#cnn #cnnimageclassification #imageclassificationpython #cnnmodel #deeplearning #tensorflowimageclassification #pythonimageclassification

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DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.
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betsynwankwo
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thank you soo much. from the knowledge i gained from this video, i decided to also increase the number of epochs in the first network(ann) from 5 to 10 and that led to a slight increase in the training accuracy(0.49 to 0.54). and for the cnn i intentionally decided first use the SDG optimizer and later the adam which also gave two different but better results than the ann. i also adjusted the epochs in each case. this has given me some more ideas to play around with, with regards to this model. once again thank you for bn such a great teacher

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REALLY A GOOD VIDEO, i finally understood implementing CNN using CIFAR10

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