Employee Attrition Prediction in Apache Spark (ML) Project


What you’ll be taught

On this course we are going to implement Spark Machine Studying Challenge Worker Attrition Prediction in Apache Spark utilizing Databricks Pocket book (Neighborhood server)

Launching Apache Spark Cluster

Course of that information utilizing a Machine Studying mannequin (Spark ML Library)

Fingers-on studying

Discover Apache Spark and Machine Studying on the Databricks platform.

Actual-time Use Case

Create a Information Pipeline

Publish the Challenge on Internet to Impress your recruiter

Description

Spark Machine Studying Challenge (Worker Attrition Prediction) for rookies utilizing Databricks Pocket book (Unofficial) (Neighborhood version Server)

On this Information science Machine Studying challenge, we are going to create Worker Attrition Prediction Challenge utilizing Choice Tree Classification algorithm one of many predictive fashions.

  • Discover Apache Spark and Machine Studying on the Databricks platform.
  • Launching Spark Cluster
  • Create a Information Pipeline
  • Course of that information utilizing a Machine Studying mannequin (Spark ML Library)
  • Fingers-on studying
  • Actual time Use Case
  • Publish the Challenge on Internet to Impress your recruiter
  • Graphical Illustration of Information utilizing Databricks pocket book.
  • Rework structured information utilizing SparkSQL and DataFrames

Worker Attrition Prediction a Actual time Use Case on Apache Spark

About Databricks:

Databricks helps you to begin writing Spark ML code immediately so you’ll be able to focus in your information issues.

English
language

Content material

Introduction

Introduction

Obtain Assets

Obtain Assets

Challenge Begins

Introduction to Spark
Free Account creation in Databricks
Provisioning a Spark Cluster
Introduction to Machine Studying
Fundamentals about notebooks
Dataframes
File Content material
Challenge Explaination Half 1
Challenge Explaination Half 2
Challenge Explaination Half 3
Challenge Explaination Half 4
Challenge Explaination Half 5
Challenge Explaination Half 6
Challenge Explaination Half 7
Challenge Explaination Half 8
Vital Lecture
Bonus Lecture

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