Employee Attrition Prediction in Apache Spark (ML) Project
Employee attrition Prediction in Apache Spark (ML) & HR Analytics Employee Attrition & Performance project for beginners
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 Workforce Data Analysis: Explore and preprocess large-scale HR datasets to uncover patterns and trends. Feature Engineering for HR: Identify and engineer key factors like job satisfaction, performance, and workload that influence employee attrition. Machine Learning Pipelines: Build scalable predictive models using Spark MLlib to forecast attrition risks. Model Optimization & Evaluation: Fine-tune your machine learning models to maximize prediction accuracy and business impact. Data-Driven Insights: Learn how to translate model predictions into actionable strategies for improving employee retention.
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.
Requirement:
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.