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Neural Networks and Applications NPTEL

Online Free Online Course by  World Mentoring Academy
Online / Free Online Course

Details

Language: English
Units: 37
Lesson content
  • Lec 1 Introduction  
  • Lec-2 Artificial Neuron Model and Linear Regression  
  • Lec-3 Gradient Descent Algorithm  
  • Lec-4 Nonlinear Activation Units and Learning Mechanisms  
  • Lec-5 Learning Mechanisms-Hebbian,Competitive,Boltzmann  
  • Lec-6 Associative memory  
  • Lec-7 Associative Memory Model  
  • Lec-8 Condition for Perfect Recall in Associative Memory  
  • Lec-9 Statistical Aspects of Learning  
  • Lec-10 V.C. Dimensions: Typical Examples  
  • Lec-11 Importance of V.C. Dimensions Structural Risk Minimization  
  • Lec-12 Single-Layer Perceptions  
  • Lec-13 Unconstrained Optimization: Gauss-Newtons Method  
  • Lec-14 Linear Least Squares Filters  
  • Lec-15 Least Mean Squares Algorithm  
  • Lec-16 Perceptron Convergence Theorem  
  • Lec-17 Bayes Classifier&Perceptron: An Analogy  
  • Lec-18 Bayes Classifier for Gaussian Distribution  
  • Lec-19 Back Propagation Algorithm  
  • Lec-20 Practical Consideration in Back Propagation Algorithm  
  • Lec-21 Solution of Non-Linearly Separable Problems Using MLP  
  • Lec-22 Heuristics For Back-Propagation  
  • Lec-23 Multi-Class Classification Using Multi-layered Perceptrons  
  • Lec-24 Radial Basis Function Networks: Cover's Theorem  
  • Lec-25 Radial Basis Function Networks: Separability&Interpolation  
  • Lec-26 Radial Basis Function as ill-Posed Surface Reconstruction  
  • Lec-27 Solution of Regularization Equation: Greens Function  
  • Lec-28 Use of Greens Function in Regularization Networks  
  • Lec-29 Regularization Networks and Generalized RBF  
  • Lec-30 Comparison Between MLP and RBF  
  • Lec-31 Learning Mechanisms in RBF  
  • Lec-32 Introduction to Principal Components and Analysis  
  • Lec-33 Dimensionality reduction Using PCA  
  • Lec-34 Hebbian-Based Principal Component Analysis  
  • Lec-35 Introduction to Self Organizing Maps  
  • Lec-36 Cooperative and Adaptive Processes in SOM  
  • Lec-37 Vector-Quantization Using SOM
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