chapter 1: distributed computing primer

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Chapter 1: Distributed Computing Primer

Chapter 2: Data Ingestion

Chapter 3: Data Cleansing and Integration

Chapter 4: Real-Time Data Analytics

Chapter 5: Scalable Machine Learning with PySpark

Chapter 6: Feature Engineering – Extraction,

Transformation, and Selection

Chapter 7: Supervised Machine Learning

Chapter 8: Unsupervised Machine Learning

Chapter 9: Machine Learning Life Cycle Management

Chapter 10: Scaling Out Single-Node Machine Learning

Using PySpark

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Chapter 11: Data Visualization with PySpark

Chapter 12: Spark SQL Primer

Chapter 13: Integrating External Tools with Spark SQL

Chapter 14: The Data Lakehouse

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