DataCamp

Introduction to Anomaly Detection in R

Engineering and Technology

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Short Description

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

Long Description

Are you seeking assistance in addressing inaccurate or suspicious records within your data? Look no further, as an anomaly detection algorithm can provide the solution you need. Anomaly detection encompasses a range of techniques specifically developed to identify atypical data points. These techniques are essential for detecting fraudulent activities and safeguarding computer networks against malicious behavior. In this course, you will delve into statistical tests that effectively identify outliers. Additionally, you will gain proficiency in utilizing advanced anomaly scoring algorithms such as the local outlier factor and isolation forest. Through practical applications, you will learn how to apply anomaly detection algorithms to identify uncommon wines within the UCI Wine quality dataset and to detect instances of thyroid disease based on abnormal hormone measurements.

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Course Details

Duration
4 hours
Format
Short Course
Price
USD39.00
Course Link
More Information
DataCamp
DataCamp
Description
DataCamp is an online learning platform that offers interactive courses and tutorials for data science and analytics. It provides a wide range of courses covering topics such as Python, R, SQL, machine learning, data visualization, and more. The platform offers a hands-on learning experience through coding exercises and projects, allowing users to practice and apply their skills in real-world scenarios. DataCamp also offers a personalized learning experience with adaptive learning technology that adjusts the course content based on the user's skill level and progress. It is widely used by individuals, professionals, and organizations to enhance their data science skills and stay up-to-date with the latest trends and technologies in the field.
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