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Distributed Deep Learning with Apache Spark

Track :

Programming

Lessons no : 6

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What will you learn in this course?
  • Implement distributed deep learning models using Apache Spark's scalable architecture and APIs in Scala, Python, Java, or R
  • Optimize large-scale deep learning workflows with Spark's execution engine and data processing capabilities
  • Integrate Spark with popular deep learning frameworks to enhance model training and deployment at scale
  • Apply Spark's data processing tools to prepare and manage big data for deep learning applications
  • Troubleshoot and debug distributed deep learning tasks within Spark environments effectively
  • Evaluate performance metrics and improve efficiency of deep learning models in distributed Spark clusters

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Lessons | 6


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Rajeshwari R M

good 2025-08-29

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Apache Spark, written in Scala, is a general-purpose distributed data processing engine. Or in other words: load big data, do computations on it in a distributed way, and then store it. Spark provides high-level APIs in Java, Scala, Python and R, and an optimized engine that supports general execution graphs .