Weight Initialization and Regularization Techniques for NNs
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- Опубліковано 25 сер 2024
- Neural Networks have a lot of knobs and buttons you have to set correctly to get the best possible performance out of it. Although some of them are self-explanatory and easy to understand (like the number of neurons in the input layer) and choose, there are many hyperparameters that are a bit more complex in terms of how they affect the outcome of the model (e.g. number of layers, the batch size or weight initialization).
In this lesson, we will learn about weight initialization techniques and regularization. We will take a look at the options for these hyperparameters and how they affect the performance of the network.
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Hello Mısra! I want to congratulate you for this great series but i also had a question. When building a neural network should we initialize the weights of all layers or just the weights of the input layer?
Hey, everything ok ?
I just noticed your videos stopped suddenly
Hope all is well
Thanks for checking in, Will! I was ill last week so I couldn't upload the videos. I'm back this week :)
@@misraturp glad to hear you're feeling better :)
@@thewilltejeda Thank you!
@@misraturp 😄