Complete Outlier Detection Algorithms A-Z: In Data Science

Complete Outlier Detection Algorithms A-Z: In Data Science, available at $44.99, has an average rating of 3.5, with 18 lectures, 1 quizzes, based on 47 reviews, and has 266 subscribers.

You will learn about Understand the fundamentals of Outliers You will learn outlier algorithms used in Data Science, Machine Learning with Python Programming You will learn both theoretical and practical knowledge, starting with basic to complex outlier algorithms You will learn approaches to modelling outliers / anomaly detection Determine how to apply a supervised learning algorithm to a classification problem for outlier detection Apply and assess a nearest-neighbor algorithm for identifying anomalies in the absence of labels Apply a supervised learning algorithm to a classification problem for anomaly and outlier detection Make judgments about which methods among a diverse set work best to identify anomalies This course is ideal for individuals who are Data Scientist or Data Analyst or Financial Analyst or Business Analyst or Software Engineers or Technical Managers or People interested in outlier detection, anomality detection, fraud detection, unseen pattern in data or People who want a career in Data Science or Data Analytics or This course targets existing data science practitioners that have expertise building machine learning models, who want to deepen their skills on outlier detection and anomality detection It is particularly useful for Data Scientist or Data Analyst or Financial Analyst or Business Analyst or Software Engineers or Technical Managers or People interested in outlier detection, anomality detection, fraud detection, unseen pattern in data or People who want a career in Data Science or Data Analytics or This course targets existing data science practitioners that have expertise building machine learning models, who want to deepen their skills on outlier detection and anomality detection.

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Summary

Title: Complete Outlier Detection Algorithms A-Z: In Data Science

Price: $44.99

Average Rating: 3.5

Number of Lectures: 18

Number of Quizzes: 1

Number of Published Lectures: 18

Number of Published Quizzes: 1

Number of Curriculum Items: 19

Number of Published Curriculum Objects: 19

Original Price: ₹3,099

Quality Status: approved

Status: Live

What You Will Learn

• Understand the fundamentals of Outliers
• You will learn outlier algorithms used in Data Science, Machine Learning with Python Programming
• You will learn both theoretical and practical knowledge, starting with basic to complex outlier algorithms
• You will learn approaches to modelling outliers / anomaly detection
• Determine how to apply a supervised learning algorithm to a classification problem for outlier detection
• Apply and assess a nearest-neighbor algorithm for identifying anomalies in the absence of labels
• Apply a supervised learning algorithm to a classification problem for anomaly and outlier detection
• Make judgments about which methods among a diverse set work best to identify anomalies

Who Should Attend

• Data Scientist or Data Analyst or Financial Analyst or Business Analyst or Software Engineers or Technical Managers
• People interested in outlier detection, anomality detection, fraud detection, unseen pattern in data
• People who want a career in Data Science or Data Analytics
• This course targets existing data science practitioners that have expertise building machine learning models, who want to deepen their skills on outlier detection and anomality detection

Target Audiences

• Data Scientist or Data Analyst or Financial Analyst or Business Analyst or Software Engineers or Technical Managers
• People interested in outlier detection, anomality detection, fraud detection, unseen pattern in data
• People who want a career in Data Science or Data Analytics
• This course targets existing data science practitioners that have expertise building machine learning models, who want to deepen their skills on outlier detection and anomality detection