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Learn Features and Dimensions : The Complete Developer Guide

Feature refers to the internal representation of the data. It is an individual measurable property or characteristic of a phenomenon being observed. Dimension simply refers to the number of features for given data. In this course, we will learn about pattern recognition using features and dimensionality reduction through various algorithms.

365 days course access

Live instructor-led online classes

Industry-based projects

Learn how Features and Dimensions plays an important role in AI and ML algorithms

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Guide from “Amphi”

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Includes:

  • 2 hours of lecture Videos
  • 60 hands-on practice exercises
  • 35 Assessment exercises
  • 15 code analysis exercises
  • 300 knowledge based questions
  • 2 Live connect sessions
             (Master classes)
  • Lifetime access
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Learn Features and Dimensions : The Complete Developer Guide

ABOUT THE COURSE

In this course, you will learn about different pattern recognition systems, data preprocessing, dimensionality reduction and component analysis and discriminants.

COURSE OBJECTIVES

Upon successful completion of the course, the learner will be able to :
  • Master the various concepts in Features and Dimensions.
  • Learn how Features and Dimensions plays an important role in AI and ML algorithms.

Course Content

Pattern Recognition Systems

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.

  • 1 Video
  • 7 hours
  • 80 Problems

Design Cycle

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.

  • 1 Video
  • 7 hours
  • 80 Problems

Data Preprocessing

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.

  • 1 Video
  • 10 hours
  • 90 Problems

Problems of Dimensionality

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.

  • 1 Video
  • 7 hours
  • 80 Problems

Component Analysis and Discriminants

In this topic, you will learn about the various Component Analysis like, PCA and the various Discriminant Analysis line, LDA and MDA.

  • 1 Video
  • 7 hours
  • 80 Problems

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