Modules / Lectures
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1Lecture 01: IntroductionDownloadDownload
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2Lecture 02: Feature Descriptor - IDownloadDownload
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3Lecture 03: Feature Descriptor - IIDownloadDownload
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4Lecture 04: Bayesian Learning - IDownloadDownload
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5Lecture 05: Bayesian Learning - IIDownloadDownload
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6Lecture 06: Discriminant Function - IDownloadPDF unavailable
7Lecture 07: Discriminant Function - IIDownloadPDF unavailable
8Lecture 08: Discriminant Function - IIIDownloadPDF unavailable
9Lecture 09: Linear ClassifierDownloadPDF unavailable
10Lecture 10: Linear Classifier - IIDownloadPDF unavailable
11Lecture 11: Support Vector Machine - IDownloadPDF unavailable
12Lecture 12: Support Vector Machine - IIDownloadPDF unavailable
13Lecture 13: Linear MachineDownloadPDF unavailable
14Lecture 14: Multiclass Support Vector Machine - IDownloadPDF unavailable
15Lecture 15: Multiclass Support Vector Machine -IIDownloadPDF unavailable
16Lecture 16: OptimizationDownloadPDF unavailable
17Lecture 17: Optimization Techniques in Machine LearningDownloadPDF unavailable
18Lecture 18: Nonlinear FunctionsDownloadPDF unavailable
19Lecture 19: Introduction to Neural NetworkDownloadPDF unavailable
20Lecture 20: Neural Network -IIDownloadPDF unavailable
21Lecture 21: Multilayer PerceptronDownloadPDF unavailable
22Lecture 22: Multilayer Perceptron - IIDownloadPDF unavailable
23Lecture 23: Backpropagation LearningDownloadPDF unavailable
24Lecture 24: Loss FunctionDownloadPDF unavailable
25Lecture 25: Backpropagation Learning- ExampleDownloadPDF unavailable
26Lecture 26: Backpropagation Learning- Example IIDownloadPDF unavailable
27Lecture 27: Backpropagation Learning- Example IIIDownloadPDF unavailable
28Lecture 28: AutoencoderDownloadPDF unavailable
29Lecture 29: Autoencoder Vs. PCA IDownloadPDF unavailable
30Lecture 30: Autoencoder Vs. PCA IIDownloadPDF unavailable
31Lecture 31: Autoencoder TrainingDownloadPDF unavailable
32Lecture 32: Autoencoder Variants IDownloadPDF unavailable
33Lecture 33: Autoencoder Variants IIDownloadPDF unavailable
34Lecture 34: ConvolutionDownloadPDF unavailable
35Lecture 35: Cross CorrelationDownloadPDF unavailable
36Lecture 36: CNN ArchitectureDownloadPDF unavailable
37Lecture 37: MLP versus CNN, Popular CNN Architecture: LeNetDownloadPDF unavailable
38Lecture 38: Popular CNN Architecture: AlexNetDownloadPDF unavailable
39Lecture 39: Popular CNN Architecture: VGG16, Transfer LearningDownloadPDF unavailable
40Lecture 40: Vanishing and Exploding GradientDownloadPDF unavailable