Types of Deep Learning Algorithms

Types of deep learning algorithms:

Deep learning algorithms run through several layers of neural networks dynamically, these layers are highly sensitive to detect low-lavel features of the image like edge and pixels and in middle some layers might be program to detect some special parts or features of an object. these layers are nothing but a set of decision making networks.
These are pre-trained to serve a specific task. Deep learning algorithms can work with almost any kind of data and it can handle the large number of processes for the data that may be strructured or unstructered.

Top 10 most popular deep learning algorithms are:
  1. 1. Convolutional Neural network(CNNs)
  2. 2. Long Short Term Memory Networks (LSTMs)
  3. 3. Recurrent Neural Networks (RNNs)
  4. 4. Generative Adversarial Networks (GANs)
  5. 5. Radial Basis Function Networks (RBFNs)
  6. 6. Multilayer Perceptrons (MLPs)
  7. 7. Self Organizing Maps (SOMs)
  8. 8. Deep Belief Networks (DBNs)
  9. 9. Restricted Boltzmann Machines( RBMs)
  10. 10. Autoencoders

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