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Employee Attrition Prediction in Apache Spark (ML) Project

Employee attrition Prediction in Apache Spark (ML) & HR Analytics Employee Attrition & Performance project for beginners

Course Description

Apache Spark Machine Learning Project (Employee Attrition Prediction) for beginners using Databricks Notebook (Unofficial) (Community edition Server) 

In this Data science Machine Learning project, we will create Employee Attrition Prediction Project using Decision Tree Classification algorithm one of the predictive models.

  • Explore Apache Spark and Machine Learning on the Databricks platform.

  • Launching Spark Cluster

  • Create a Data Pipeline

  • Process that data using a Machine Learning model (Spark ML Library)

  • Hands-on learning

  • Real time Use Case 

  • Publish the Project on Web to Impress your recruiter 

  • Graphical Representation of Data using Databricks notebook.

  • Transform structured data using SparkSQL and DataFrames


Employee Attrition Prediction a Real time Use Case on Apache Spark

About Databricks: 

Databricks lets you start writing Spark ML code instantly so you can focus on your data problems.

Goals

  • In this course you will implement Spark Machine Learning Project Employee Attrition Prediction in Apache Spark using Databricks Notebook (Community edition server)
  • Launching Apache Spark Cluster
  • Process that data using a Machine Learning model (Spark ML Library)
  • Hands-on learning
  • Explore Apache Spark and Machine Learning on the Databricks platform.
  • Real-time Use Case
  • Create a Data Pipeline

Prerequisites

  • Apache Spark basic and Scala fundamental knowledge is required and SQL Basics along with Machine Learning basics
  • Following browsers on Windows, Linux or macOS desktop:
  • Google Chrome (Latest version), Firefox (Latest version), Safari (Latest version), Microsoft Edge* (Latest version)
  • Internet Explorer 11* on Windows 7, 8, or 10 (with latest Windows updates applied)
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Curriculum

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Employee Attrition Prediction in Apache Spark (ML) Project
This Course Includes
  • 2 hours
  • 21 Lectures
  • 2 Resources
  • Completion Certificate Sample Certificate
  • Lifetime Access Yes
  • Language English
  • 30-Days Money Back Guarantee

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