How to determine what type of layers do I need for my Deep learning model?

Admin 1
Viewed 132

Suppose that I have want to make a model that does something. Now when I search about the topic in Google or YouTube, I find many related tutorials and it seems like some clever programmer had already implemented that model with Deep learning.

But how do they know that what type of layers, what type of activation functions, loss functions, optimizer, number of units etc. they need to solve that certain problem using deep learning.

Are there any techniques for knowing this, or its just a matter of understanding and experience? Also it would be very helpful if somebody could point me to some videos or articles answering my question.

tflearn keras tensorflow deep-learning
2 Answers

This is more of a matter of understanding and experience. When building a model from scratch, you must understand which optimizer, loss, etc. makes sense for your particular problem. In order to choose these appropriately, you must understand the differences between the available optimizers, loss functions, etc.

In regards to choosing how many layers and nodes, what batch size, what learning rate, etc.-- these are all hyperparameters that you will need to test and tune as you experiment with your model.

I have a Deep Learning Fundamentals YouTube playlist that you may find helpful. It covers the fundamental basics of each of these topics in short videos. Additionally, this Deep Learning with Keras playlist may also be beneficial if you're wanting to focus more on coding after getting the basic concepts down.

user_83289700

Thanks for the question.

  1. The CS231n Stanford lectures on CNN is the best for beginners refer to the video lectures here and class notes are available here
  2. After watching the lectures and completing the assignments, you will get a basic idea of what Deep Learning is and all the algorithms available etc.
  3. But when it comes to solving real-world problems this won't be sufficient So take this course by Jeremy Howard where he teaches more on how to approach a problem using Kaggle platform.
  4. Keep on solving more problems experimenting new models and algorithms using several platforms like hackerearth, Kaggle, topcoder etc.
user_85804780
Related