ABOUT THE COURSEIn this course, you will learn about different pattern recognition systems, data preprocessing, dimensionality reduction and component analysis and discriminants.
COURSE OBJECTIVESUpon successful completion of the course, the learner will be able to :
In this topic, you will learn about Different Pattern Recognition Systems and Different steps to follow Pattern Recognition, like, Sensing, Segmentation, Grouping, Feature Extraction, Classification and Post Processing.
In this topic, you will learn about the design cycle in Pattern Recognition and the different states in the design cycle like, Data Collection, Feature Choice, Model Choice, Training, Evaluation and Complexity analysis.
In this topic, you will learn about the different data processing techniques, which involve, Descriptive Data Summarization, Data Cleaning, Data Integration and Transformation, and Data Reduction.
In this topic, you will learn about the various problems that arises due to high dimensional data, with respect to Accuracy and Complexity and how an increase in the number of features lead to Overfitting of the Component.
In this topic, you will learn about the various Component Analysis like, PCA and the various Discriminant Analysis line, LDA and MDA.
You can opt for the following courses once you complete your ongoing course
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