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Classroom Contents
Azure Databricks Using Python With PySpark
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- 1 Introduction
- 2 Background
- 3 Scaleout
- 4 DataFrame API
- 5 RDD vs DataFrame
- 6 PySpark API
- 7 PySpark
- 8 Scaling out ML
- 9 Notebook setup
- 10 Importing data
- 11 Python vs SQL
- 12 Creating persistent tables
- 13 Renaming columns
- 14 Pandas
- 15 Display
- 16 DropN
- 17 Exploring the Data
- 18 Persistence
- 19 Visualizations
- 20 More Data
- 21 Case Statements
- 22 Spark Sequel
- 23 Matplotlib
- 24 Adding a new column
- 25 Adding a new dataframe
- 26 Userdefined functions
- 27 Local Python dataframe
- 28 ML Live
- 29 Building the Model
- 30 Writing the Model
