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Pattern Recognition
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Pattern Recognition
by Prof Sukhendu Das

Pattern recognition is the automated recognition of patterns and regularities in data. Pattern recognition is closely related to artificial intelligence and machine learning, together with applications such as data mining and knowledge discovery in databases, and is often used interchangeably with these terms....

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level English
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Program Fee
FREE
About This Course

Pattern recognition is the automated recognition of patterns and regularities in data. Pattern recognition is closely related to artificial intelligence and machine learning, together with applications such as data mining and knowledge discovery in databases, and is often used interchangeably with these terms....


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Course Curriculum
6 Sections | 30 Lecture | 19h 04min total length
Expand all sections
Pattern Recognition

Classification

| 01h 47min total length
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    Assignments

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    Gaussian Mixture Model (GMM)

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    Assignments

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Pattern Recognition

Clustering

| 01h 59min total length
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    Basics of Clustering, Similarity/Dissimilarity Measures, Clustering Criteria.?

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    K-Means Algorithm and Hierarchical Clustering?

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    K-Medoids and DBSCAN

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Pattern Recognition

Feature Selection

| 04h 42min total length
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    Feature Selection : Problem statement and Uses

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    Feature Selection : Branch and Bound Algorithm

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    Feature Selection : Sequential Forward and Backward Selection

    47m <?php echo $alt; ?>
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    Cauchy Schwartz Inequality

    47m <?php echo $alt; ?>
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    Feature Selection Criteria Function: Probabilistic Separability Based

    47m <?php echo $alt; ?>
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    Feature Selection Criteria Function: Interclass Distance Based

    47m <?php echo $alt; ?>
Pattern Recognition

Feature Extraction

| 50min 48sec total length
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    Principal Components

    50m <?php echo $alt; ?>
Pattern Recognition

Introduction and mathematical Preliminaries

| 04h 33min total length
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    Vector Spaces

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    Eigen Value and Eigen Vectors

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    Rank of Matrix and SVD

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    Relevant Basics of Linear Algebra, Vector Spaces

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    Clustering vs. Classification

    33m <?php echo $alt; ?>
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    Principles of Pattern Recognition II (Mathematics)

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    Principles of Pattern Recognition III (Classification and Bayes Decision Rule)

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    Principles of Pattern Recognition I (Introduction and Uses)

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Pattern Recognition

Recent Advances in pattern Recognition

| 05h 10min total length
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    Comparison Between Performance of Classifiers

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    Examples of Real-Life Dataset

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    Examples of Uses or Application of Pattern Recognition; And When to do clustering

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    FCM and Soft-Computing Techniques?

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    Support Vector Machine (SVM)

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    Visualization and Aggregation

    34m <?php echo $alt; ?>
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    Probability Density Estimation

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    Data Condensation, Feature Clustering, Data Visualization

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    Basics of Statistics, Covariance, and their Properties

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show 3 more sections
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