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Real-time Credit card Fraud Detection using Spark 22

Learners: 4,387

Instructor: Pramod Narayana

Duration:

This course provides an in-depth look at how to detect credit card fraud in real-time using Spark, Kafka, and Cassandra. It covers the use of Spark ML Pipeline Stages such as String Indexer, One Hot Encoder, and Vector Assembler for pre-processing, Random Forest Algorithm for machine learning, K-means Algorithm for data balancing, and Spark Streaming custom offset management for exactly-once semantics. Finally, it covers the use of Airflow Automation framework to automate Spark Jobs on a Spark Standalone Cluster.▼▲

Course Feature Course Overview Course Provider

Go to class

Course Feature

Cost:

Paid

Provider:

Udemy

Certificate:

Paid Certification

Language:

English

Start Date:

2019-11-13

Course Overview

❗The content presented here is sourced directly from Udemy platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [July 25th, 2023]

This course provides an introduction to Real-time Credit card Fraud Detection using Spark, Kafka and Cassandra. Students will learn how to use Spark ML Pipeline Stages such as String Indexer, One Hot Encoder and Vector Assembler for pre-processing. The Random Forest Algorithm will be used to create a Machine Learning model, and K-means Algorithm will be used for data balancing. Additionally, students will learn how to integrate a Spark Streaming Job with Kafka and Cassandra, and how to achieve exactly-once semantics using Spark Streaming custom offset management. Finally, students will be introduced to the Airflow Automation framework, which can be used to automate Spark Jobs on a Spark Standalone Cluster.