Transfer Learning Using Keras(ResNet-50)| Complete Python Tutorial|

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In this video i show you you can use the keras and tensorflow library to implement transfer learning for any of your image classification problems in python.
Transfer learning allows you to use weights learnt by state of the art convolutional neural networks or CNN like Resnet, Inception or VGG and fine tune it for your image data.

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the most no-nonsense straight to the point video on resnet video, keep up the good work!

leoyuanluo

Very concise down to the point summary, no redundant words and tedious good-for-nothing introductions. Thanks!

AndreyKatz

I've been trying to implement resnet for days, finally this has helped me. Thank you so much :)

prathyushaa

Great Resource.

As the rookie in the Machine Learning field, this is really practical exercise for the one who wants to integrate ResNet (Not only this, but also other model as he mentions in here) model to the Sequential layers.

literacy_

Thanks for this, it was very helpful. I just had to change the import lines to deal with a newer version of keras.

keithwetton

Thank you very much, I've trying to implement ResNet for a long time, this video really helped me. Please upload more videos :)

fabiofiestas

Thank you so much for the content! This really helped me understand how to fine-tune a model in one of my projects :)

alexisbaladon

Thanks to this video I discovered your amazing channel! Thank you Nachiketa, You are the man! Thanks a lot for all your efforts, trully appreciated from the other side of the world. Please keep this amazing job, God bless you my friend.

josemariovalenciahenao

bro i learned this for 1 semester and you just explained it in 10 minutes....and i understand it. how

matildabich

Hi, how can I save the model?
When I do it gives me an error.
I searched information about it but I do not know how to solve It.
The error is: Layer ModuleWrapper was created by passing
non-serializable argument values in `__init__()`,
and therefore the layer must override `get_config()` in
order to be serializable. Please implement `get_config()`.

mikilmku

Hey, great video, thank you very much for the explanation and material.
I needed to put the loss function to because otherwise it said shape value error.

Liz_

Thanks for the video!! It was really handy for my project!!

herberthipolito

hi make a video on anamoly detection. using python on time series data. to detect node tampering

Paattiil

I'm confused why there is only training and validation. Why is there not also a testing dataset? Isn't validation data used to optimize hyperparameters only? It seems you're using the validation data to evaluate accuracy. Is this normal?

harvardyard

I'm getting an error saying "This model has not yet been built. Build the model first by calling `build()` or calling `fit()` with some data, or specify an `input_shape` argument in the first layer(s) for automatic build."
what should I do?

vikneshrajan

Thank you, Can you write a code in keras.application and the weights aren't 'imagenet' ?

mahdifarhadi

Thanks Bhai kafi din se pareshan tha me Resnet ko le kr

shariqueansari

Brother iam very displeased with you. What kind of explanation is that. Who does that. How can your explanation be so easy to understand. Iam displeased coz why didn't I see your videos till this time. But now iam happy that i got someone who explains like others understand. Congrats for a new subscriber.

maaleem

Thank you for this! Wonderful explanation

mums

hello my friend. i am planning to use resnet50 for my project. basically the project is about birads classification. i have dataset which has around 3000 images and 3 classes (birads2, birads4, birads5). i want this model to classify the mammography pictures as birads classification. i tried to fine tune this model but it didn't really work. do you have any suggestions or hints for me to tune this model for such a detailed and complicated birads classification?

ahmetberkay

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