Deep Learning (from basics)

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Following topics are covered as part of the course

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  Explore building blocks of neural networks
  
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    Data representation, Tensor, Back propagation
    
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  Keras
  
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    Dataset, Applying Keras to cases studies, over fitting / under fitting
    
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  Artificial Neural Networks (ANN)
  
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    Activation functions
    
    
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    Loss functions
    
    
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    Gradient Descent
    
    
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    Optimizer
    
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  Image Processing
  
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    Convnets (CNN), hands-on with CNN
    
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  Text and Sequences
  
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    Text data, Language Processing
    
    
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    Recurrent Neural Network (RNN)
    
    
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    LSTM
    
    
  • 
    Bidirectional RNN
    

• 
  Gradients and Back Propagation – Mathematics
  

Instructors: Shrirang Korde




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