Answers.Body: <p>I don't think there is a fixed threshold that differentiates between Shallow and Deep Learning, but I would say that a 2 layer NN should not be considered deep. But now-a-days, almost all NN architectures are studied under the umbrella of Deep Learning.</p>
  <p>And yes, training a 2 hidden layers NN using Q-learning would technically mean doing deep RL.</p>
  <p>I guess it is conceptually simple but making NN perform optimally is an art. Tuning hyperparameters or debugging NN can be tough and one learns with experience. I guess others in the community would be much more suited to answer this question. But these were my 2 cents.</p>
  
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Answers.CreationDate: 2020-07-01T04:23:24.090Z
Answers.LastActivityDate: 2020-07-01T04:23:24.090Z
Answers.UserDisplayName: pecey
Body: <p>I just learned the math behind neural networks so please bear with my ignorance. I wonder if there is a precise definition for DNN.</p>
  <p>Is it true that any neural network with more than 2 hidden layers can be named as a DNN, and training a NN with 2 hidden layers using Q-learning we are technically doing a type of deep reinforcement learning?</p>
  <p>PS: If it is conceptually that simple why do common people regard deep learning as something done by archmages in ivory towers.</p>
  
Tags: <neural-networks><deep-learning><deep-rl><terminology>
Title: A neural network with 2 or more hidden layers is a DNN?
UserDisplayName: High GPA
ThreadText: # A neural network with 2 or more hidden layers is a DNN?
  
  (Asked by: username_0 on 2020-07-01)
  
  I just learned the math behind neural networks so please bear with my ignorance. I wonder if there is a precise definition for DNN.
  
  Is it true that any neural network with more than 2 hidden layers can be named as a DNN, and training a NN with 2 hidden layers using Q-learning we are technically doing a type of deep reinforcement learning?
  
  PS: If it is conceptually that simple why do common people regard deep learning as something done by archmages in ivory towers.
  
  **Tags:** neural-networks, deep-learning, deep-rl, terminology
  
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  ## 1 answers
  
  ### Answer by username_1 on 2020-07-01. Score: 1 | Accepted answer
  
  I don't think there is a fixed threshold that differentiates between Shallow and Deep Learning, but I would say that a 2 layer NN should not be considered deep. But now-a-days, almost all NN architectures are studied under the umbrella of Deep Learning.
  
  And yes, training a 2 hidden layers NN using Q-learning would technically mean doing deep RL.
  
  I guess it is conceptually simple but making NN perform optimally is an art. Tuning hyperparameters or debugging NN can be tough and one learns with experience. I guess others in the community would be much more suited to answer this question. But these were my 2 cents.
  
  
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