Machine Learning with Spark ML
.MP4, AVC, 1920x1080, 30 fps | English, AAC, 2 Ch | 2h 7m | 454 MB
Instructor: Ivan Mushketyk
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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