Anomaly detection with TensorFlow | Workshop

preview_player
Показать описание
Learn how to go from basic Keras Sequential models to more complex models using the subclassing API, and see how to build an autoencoder and use it for anomaly detection with an electrocardiogram dataset to find abnormal heart rhythms.

Resources:

Speaker: Laurence Moroney

Watch more:

#GoogleIO #AI #ML

product: TensorFlow - General; event: Google I/O 2021; fullname: Laurence Moroney; re_ty: Livestream;
Рекомендации по теме
Комментарии
Автор

Fantastic video! You made neural networks very simple to understand.

cantblockjo
Автор

Simply awesome!!! Thank you so much Laurence, it's always a pleasure to learn from you!!

thiagoribeiro
Автор

nice workshop love the explanation, and the materials given

eng-khalil
Автор

What a great learning experience! Thank you Laurence Moroney

rommeltito
Автор

Awesome content, very helpful for my research. More of this.

TheMegaEzio
Автор

Excellent video and thanks a lot! Please allow me to make a question. Is the method shown in the video recommended to train and detect anomalies in financial transactions? Is the way of comparing the transaction against a previously calculated threshold recommended, or do you recommend any other I can use?
I am new in ML, so if you know any example I can use would be incredibly appreciated.

lfmtube
Автор

I love Generative modeling and your teaching style!

nitishthakur
Автор

Great content and well designed example on using an autoencoder for anomaly detection.

GeorgeZoto
Автор

Hello, could you please let me know what should be the value of dense layer like 32, 16, 8 if we have only 8 variables instead of 140 as ECG indicators??

prasadkakade
Автор

Hi! Thanks for the great content! Is it necessary for the decoder to mirror the encoder? Why does it mirror the layers of the encoder?

LazySnake
Автор

Amazing, thanks for sharing your knowledge with us!

jeremysapienza
Автор

Hi, first of all, thank you very much for the content. My question is if this would be possible with a simple classification model. If so, what are the pros and cons of each approach? Thanks in advance

PedroAcacio
Автор

This use of generative AI is just brilliant!

timoose
Автор

Thank you Laurence. People would naturally worry about the 3 false negatives that happen to show low losses. Is there any remedy for that?

Max-eovx
Автор

Thanks for the great content, Please if anyone could help in this, I have not understant why the python the dens layer started with 128 input and not 784?

SaifAhmed
Автор

Thank you for teaching this! I was confused for a long time...

lzdps
Автор

He is my teacher in coursera. Awesome Teacher. He teach me with Andrew Ng

hdm_vision
Автор

The 45 mins workshop are really good. Please continue to make more of these workshops.

jaggyjut
Автор

At 34mins 31s under the history code section, shouldn't the validation_data be using normal_test_data instead?

jonathonyee
Автор

Sir, would you like to suggest any book of tensorflow in which I could learn topics such as # Kalman Filter # BERT # LSTM and other advance topics

shariqueansari