Employee Attrition Prediction in Apache Spark (ML) Project
What you'll learn
- In this course we will implement Spark Machine Learning Project Employee Attrition Prediction in Apache Spark using Databricks Notebook (Community 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
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](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 3.9 Instructor Rating
- 614 Reviews
- 54,927 Students
- 23 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!!