People Innovation Excellence
 

ARTIFICIAL NEURAL NETWORK (2/2 Credits)

Learning Outcomes:

On successful completion of this course, students will be able to: Explain the concept of neural network; Analyze several cases using the concept of neural network; Solve problems using neural network models; Create applications using the concept of neural network.

Topics:

  1. Introduction to Python
  2. Perceptron and LMS with Python
  3. Backpropagation Neural Network with Tensorflow
  4. BPNN Parameter Tuning
  5. Quiz 1
  6. RNN Parameter Tuning
  7. Self-Organizing Map
  8. Quiz 2
  9. Principal Component Analysis
  10. CNN
  11. Project
  12. Introduction to Artificial Neural Network
  13. Single Layer Perceptron
  14. Multilayer Feedforward Neural Network 1
  15. Multilayer Feedforward Neural Network 2
  16. Self Organizing Map (SOM) 1
  17. Self Organizing Map (SOM) 2
  18. Principal Component Analysis (PCA)
  19. Convolution Neural Network (CNN) 1
  20. Convolution Neural Network (CNN) 2
  21. Review
  22. Performance Evaluation
  23. Recurrent Neural Network 1
  24. Recurrent Neural Network 2

 


Published at : Updated

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