PyTorch - The Basics of Transfer Learning with TorchVision and AlexNet

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PyTorch - The Basics of Transfer Learning with TorchVision and AlexNet

Рет қаралды 8,255

Күн бұрын

Basic usage of PyTorch. From simple low-level usage of Adagrad to building up your neural networks with the model.nn module from PyTorch. In this video we look at how to use a pre-trained AlexNet for transfer learning. We do so by removing the last layer of the network, and retraining the weights from our own small dataset.
Notebooks: github.com/mad...
Original blogpost link: www.learnopenc...
PyTorch playlist: • PyTorch - The Basics
Deep Learning introduction playlist: • Deep Learning: Part1 -...

Пікірлер: 22

@observor-ds3ro 2 ай бұрын

That was excellent! a great help for me , you described as clear and clean as possible

@vivian_who 3 жыл бұрын

Thank you very much for this! I am currently doing my undergrad thesis in PyTorch and freaking out. Your explanation is quite clear and helpful. Keep going ^^

@tudoronrec Жыл бұрын

same :D

@tudoronrec Жыл бұрын

Thank you for the information!

@kvdiatpune8753 Жыл бұрын

Thanks ,nicely explained

@murtazajabalpurwala8124 2 жыл бұрын

Hi thanx for the video, appriciate it, but I believe this tutorial was more suited for a moderate level to advanced level. I still had many concepts to dig and I thought you were skipping on many things that were still new to me. May be you can make another video where you can guide data loading process and training process more in details. Thanx again

@DennisMadsen 2 жыл бұрын

Noted. Thanks for the input Murtaza :)

@tycstahX 3 жыл бұрын

Great stuff!

@BudgiePanic 10 ай бұрын

nice

@shinchannohara3927 5 ай бұрын

will the same code with num-out 200 work for 200 class classification with such great accuracy

@mightylearning Жыл бұрын

when i am going to train vgg model with 38 classes then that error occur: RuntimeError: Given groups=1, weight of size [64, 3, 3, 3], expected input[2, 38, 224, 224] to have 3 channels, but got 38 channels instead, when i use summarytool, how to slove the error

@user-cc4rq5py1h 11 ай бұрын

unable to train my data

@user-ot6yk6ie2f Жыл бұрын

i can save this model as usual (by using alexnet) and use it with other model on open cv right?

@vikramrs4191 2 жыл бұрын

Is there an example how we can use our own trained models in transfer learning of other images in keras library

@danielac520 3 жыл бұрын

hi! which is the difference between freezing the layers or using model.eval()?

@DennisMadsen 3 жыл бұрын

Hi. In eval mode you notify all the layers that you are not in training mode. Which also has an impact on e.g. dropout and batchnorm layers. With no_grad (freeze) - this is often used for training to avoid computing the gradient for X number of layers. But indeed the goal of the two functions looks a bit the same - do not compute the gradient.

@danielac520 3 жыл бұрын

@@DennisMadsen Thanks for your answer! I understand, Anyway computing the gradient does not imply the update of parameters right ?

@DennisMadsen 3 жыл бұрын

@@danielac520 Glad it was helpful. And true. The parameters are not updated when the gradients are. You would then need to update them with something like: optimizer.step()

@danielac520 3 жыл бұрын

@@DennisMadsen Got it :)