Employee attrition Prediction in Apache Spark (ML) & HR Analytics Employee Attrition & Performance project for beginners
What you will learn
Get Instant Notification of New Courses on our Telegram channel.
Noteβ Make sure your ππππ¦π² cart has only this course you're going to enroll it now, Remove all other courses from the ππππ¦π² cart before Enrolling!
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.
English
language