How to Find the Right number of Layers/Neurons for your Neural Network?

1. How to identify how many layers are right for your architecture?
2. How to perform sensitivity analysis for your architecture to know if you got the right number of neurons / layers?
3. Learning is impacted by the number of neurons & layers for your architecture?
4. Signatures of Accuracy / MAPE convergences and error convergences with changes to neurons/layers in your architecture.
All with this hands on step by step implementation in Python & Keras.
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[@jafetsierra1875]

Very helpful, i think this is an important subject, since there's no a simple way of choosing the correct number of layers or neurons, specially for larges architectures.

[@stefanmisanovic3341]

Great video, very helpful to get ideas how to visualize the accuracy of a model and how to automate the process.

[@machinelearningmastery]

Glad to know it was helpful. :-) please spread the word.

[@JLBorloo]

Good stuff but consider sharing the Notebooks in the future

[@kevinchaplin672]

Very nice, clear and concise

[@machinelearningmastery]

Thank you.

[@agc444]

Wonderful video, many thanks. Perhaps it would be nice if you made the code available for us learners to play with. Thanks.

[@hatemmohamed8387]

is there any repo containing the codes for the entire playlist

[@skullywully653]

would it be possible for me to grab that code somewhere?

[@machinelearningmastery]

I have gone over the code in the video. Any particular segment not clear?

[@mshika2150]

can i get the code ?

[@chinmayb172]

Can you please tell me if I have 10 classes of training data, what number of epochs should I use?

[@machinelearningmastery]

In general, I recommend that we set epochs to very large value say 50,000.
Then in your code you setup early exit logic as part of training.
This will work best for most cases since the training fit will automatically exit when convergence has happened. Hope that helps.

[@SBhupendraAdhikari]

very helpful

[@machinelearningmastery]

Glad to hear that

[@rohitsingh-ng2tk]

G8 video

[@machinelearningmastery]

Thank you. I am glad it was helpful. Please like & share.