•  Artificial Neural Network

  TAs::

athar.mahmudi@gmail.com   

Ms. Athar Mahmoudi: athar[dot]mahmudi[at]Gmail

Mr. Hossein Asadi: hossein[dot]asadi[dot]p[at]Gmail

Mr. Ehsan Haghdoust: Ehsan[UnderLine]haggdoust[at]outlook[dot]com

group:sbu-ann-94

• Course syllabus

•  Schedule of Homeworks

• Mid Term Scores
• Final Exam Scores

• Final Scores

 

 

 

• Lecture 0 (Preliminaries) 17 Bahman 94

• Lecture 1 (Introduction, Perceptron, Learning, Adaline and Gradient descent) 21 Farvardin 95

• Lecture 2 (MLP, Back propagation) 17 Bahman 94 21 Farvardin 95

• Lecture 3 (RBF; Radial Basis Function) 17 Bahman 94 21 Farvardin 95

• Lecture 4 (SVM; Support Vector Machine) 19 Esfand 94 22 Farvardin 95

• Lecture 5 (Competitve Networks) 19 Esfand 94 29 Farvardin 95

• Lecture 6 (ART1; Adaptive resonance theory) 29 Farvardin 95 5 Ordibehesht 95

• Lecture 7 (Hopfield Network) 25 Ordibehesht 9525 Ordibehesht 95

• Lecture 8 (DNN; Deep Neural Networks) 25 Ordibehesht 95

 

 

•  Policies

• Homework 1    required data

• Homework 2     required data

• Homework 3     required data