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.