chapter 1: distributed computing primer
TRANSCRIPT
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
