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Lecture 17: Optimization Techniques in Machine Learning, by P.K. Biswas

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Neural Networks for Pattern Recognition (Contd.), by P.K. Biswas

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Image Segmentation-III, by P.K. Biswas

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Lecture 12: Image Formation-II, by P.K. Biswas

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Image Digitization I, by P.K. Biswas

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K-L Transform, by P.K. Biswas

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Image Restoration-III, by P.K. Biswas

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Lecture 40: Vanishing and Exploding Gradient, by P.K. Biswas

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Lecture 03: Feature Descriptor-II, by P.K. Biswas

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Lecture 11: Image Formation-I, by P.K. Biswas

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Pixels Relationships II, by P.K. Biswas

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Object Representation and Description-III, by P.K. Biswas

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Lecture 47 : Other Restoration Techniques-II, by P.K. Biswas

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Lecture 53 : Conversion of one Color Model to another-II, by P.K. Biswas

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Cache Memory Architecture, by P.K. Biswas

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Lecture 10: Linear Classifier-II, by P.K. Biswas

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Lecture 43 : Optimisers: Momentum and Nesterov Accelerated Gradient (NAG) Optimiser, by P.K. Biswas

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Perceptron Criterion, by P.K. Biswas

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Introduction to Digital Computer Organization, by P.K. Biswas

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Normal Density and Discriminant Function, by P.K. Biswas

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Lecture 50: Training Trick, Regularization,Early Stopping, by P.K. Biswas

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Error Detection and Correction, by P.K. Biswas

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Lecture 56 : Image Denoising, by P.K. Biswas

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Lecture 03: Image Digitalization, Sampling Quantization and Display, by P.K. Biswas

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Memory Organization-I, by P.K. Biswas

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Clustering (Contd.), by P.K. Biswas

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MSE Criterion, by P.K. Biswas

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Lecture 45 : Optimisers: Rmsprop, AdaDelta and Adam Optimiser, by P.K. Biswas

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Multiple Discriminant Analysis (Tutorial), by P.K. Biswas

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Colour Image Processing-I, by P.K. Biswas

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