Anomaly Detection in R

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Course Features

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Duration

4 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Teaching Type

Self Paced

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Video Content

4 hours

Course Description

Are you concerned about inaccurate or suspicious records in your data? An anomaly detection algorithm could be the solution. One of many methods that can be used for detecting unusual data points is the anomaly detection algorithm. It is crucial in protecting computer networks from malicious activity and detecting fraudulent activities. This course will show you how to use advanced algorithms for anomaly scoring such as the isolation factor and local outlier factors. The UCI Wine Quality dataset will contain anomaly detection algorithms that can be used to identify wines with unusual characteristics and detect thyroid disease cases based on abnormal hormone measurements.

Course Overview

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Virtual Labs

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International Faculty

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Post Course Interactions

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Hands-On Training,Instructor-Moderated Discussions

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Case Studies, Captstone Projects

Skills You Will Gain

Prerequisites/Requirements

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Intermediate R

What You Will Learn

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Learn statistical tests for identifying outliers and how to use sophisticated anomaly scoring algorithms

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In this course, you'll explore statistical tests for identifying outliers, and learn to use sophisticated anomaly scoring algorithms like the local outlier factor and isolation forest

Course Instructors

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DataCamp Content Creator

Course Instructor

DataCamp offers interactive R, Python, Spreadsheets, SQL and shell courses. All on topics in data science, statistics, and machine learning. Learn from a team of expert teachers in the comfort of you...

Course Reviews

Average Rating Based on 3 reviews

5.0

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Course Cover

$12

$6

49% OFF

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