How to Utilize Pre-Trained Models for building Deep Learning Models | VGG16 ResNET Object Detection

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This video explains how to utilize existing pre-trained models such VGG16, VGG19 or ResNET to build our own Deep Learning (CNN) Model. A method which is known as Transfer Learning. Deep learning models such as convolutional neural network models may take days or even weeks to train on the large image datasets. If we want to cut short this high model training time then we can use pre-trained models such as VGG16, VGG19, ResNet50, Inception V3, and Xception, some of them which are trained on imagenet dataset. These models were developed for the ImageNet competition and built to predict one of a thousand different classes.

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Trivia question from the video: State True or False - Using the steps shown in the video you can tweak any existing CNN or RNN pre-trained model.

TheAIUniversity

Thank you so much the best explanation of pre-trained model

annmaryshaju

thanks. now you have added 2 outputs: one for airplane and one for car. how do you train more images on top of VGG16?

spicytuna

Can we use pre-trained models to classify if there is a bubble in water or not?

shravyasweety

Does this work for all keras models or just vgg16?

goodnewsamieghemen

False, probably bcoz RNN depends on previous values ( memory) which will be different for different problems and datasets.

sckeshari

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