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Development Data Science Apache Spark

Employee Attrition Prediction in Apache Spark (ML) Project

Employee attrition Prediction in Apache Spark (ML) & HR Analytics Employee Attrition & Performance project for beginners
Rating: 3.0 out of 53.0 (7 ratings)
60 students
Created by Bigdata Engineer
Last updated 2/2021
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • 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
  • Publish the Project on Web to Impress your recruiter

Course content

3 sections • 19 lectures • 2h 19m total length

  • Preview05:30

  • Download Resources
    00:04

  • Preview04:17
  • Free Account creation in Databricks
    01:51
  • Provisioning a Spark Cluster
    02:15
  • Preview08:29
  • Basics about notebooks
    07:29
  • Dataframes
    04:47
  • File Content
    06:33
  • Project Explaination Part 1
    06:13
  • Project Explaination Part 2
    13:56
  • Project Explaination Part 3
    06:10
  • Project Explaination Part 4
    15:14
  • Project Explaination Part 5
    06:48
  • Project Explaination Part 6
    10:06
  • Project Explaination Part 7
    10:30
  • Project Explaination Part 8
    28:27
  • Important Lecture
    00:20
  • Bonus Lecture
    00:52

Requirements

  • 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)
  • *You might see performance degradation for some features on Microsoft Edge and Internet Explorer.
  • The following browsers are not supported:
  • Mobile browsers.
  • Beta, “preview,” or otherwise pre-release versions of desktop browsers.

Description

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.

Who this course is for:

  • Beginner Apache Spark Developer, Bigdata Engineers or Developers, Software Developer, Machine Learning Engineer, Data Scientist

Instructor

Bigdata Engineer
Bigdata Engineer
Bigdata Engineer
  • 3.4 Instructor Rating
  • 264 Reviews
  • 15,305 Students
  • 20 Courses

I am Solution Architect with 12+ year’s of experience in Banking, Telecommunication and Financial Services industry across a diverse range of roles in Credit Card, Payments, Data Warehouse and Data Center programmes

My role as Bigdata and Cloud Architect to work as part of Bigdata team to provide Software Solution.

Responsibilities includes,

- Support all Hadoop related issues
- Benchmark existing systems, Analyse existing system challenges/bottlenecks and Propose right solutions to eliminate them based on various Big Data technologies
- Analyse and Define pros and cons of various technologies and platforms
- Define use cases, solutions and recommendations
- Define Big Data strategy
- Perform detailed analysis of business problems and technical environments
- Define pragmatic Big Data solution based on customer requirements analysis
- Define pragmatic Big Data Cluster recommendations
- Educate customers on various Big Data technologies to help them understand pros and cons of Big Data
- Data Governance
- Build Tools to improve developer productivity and implement standard practices

I am sure the knowledge in these courses can give you extra power to win in life.

All the best!!

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