• views: 70
• date: 7 September 2025
• posted by: AD-TEAM

Learn how to use Spark ML to build scalable machine learning solutions. Get hands-on with regression, classification, feature engineering, model evaluation, hyperparameter tuning and more, plus learn deep learning integration with Apache Spark.

What you'll learn

• Use Spark ML to build scalable machine learning models
  
• Apply regression and classification algorithms
  
• Apply feature engineering techniques at scale
  
• Evaluate model performance with the right metrics
  
• Optimize models through hyperparameter tuning
  
• Integrate deep learning tools with Spark
  
• Handle big data Machine Learning workflows efficiently
  
• Build production-ready Machine Learning pipelines
  

Machine learning doesn't stop at theory.it needs to scale. In this course, you'll learn how to take ML models to production-level scale using Spark ML.

We'll dive into hands-on techniques for regression and classification, explore smart feature engineering, and show you how to evaluate and tune models for real performance. You'll also get a glimpse of how deep learning can plug into your Spark workflows.

If you're ready to stop experimenting and start building, this is where it happens.

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