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Deep-Learning-Models

Deep Learning Models implemented in python using numpy arrays.
Inspired by Deep learning repository https://github.com/yusugomori/DeepLearning/tree/master/cpp

Files added:

  1. fucntions.py - Contains the necessary functions for the models. It will be updated frequently as the functions are used in the uploaded files.
  2. RBM.py - Restricted Boltzmann Machine. (A Boltzmann Machine with 2 bipartite layers (visible and hidden)
  3. HL.py - Hidden Layer : The layers above the input layers.
  4. LR.py - Logistic regression class.
  5. DBN.py - Deep Belief Nets, A multi layer Restricted Boltzmann Machine.
  6. CRBM.py - Restricted Boltzmann Machine with continuous valued-inputs. Extends the RBM to capture temporal dependencies.
  7. CDBN.py - Deep Belief Nets with continued value points input.
  8. MLP.py - Multi Layer Perceptron.
  9. dA.py - Denoising Autoencoder.
  10. SdA.py - Stacked denoising Autoencoders.
  11. CPL.py - Convolution and Max Pooling.
  12. CNN.py - Convolutional Neural Network.
  13. SVM.py - Support Vector Machine.