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Catching Errors
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Classroom Contents
Machine Learning with Scala on Spark
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- 1 Introduction
- 2 Definition of Machine Learning
- 3 Why talk about Machine Learning
- 4 Not happening is bad
- 5 Prediction
- 6 Software Industries
- 7 Machine Learning
- 8 Why do people do this
- 9 Why is DSR doing this
- 10 Python
- 11 Scala
- 12 Scala vs Spark
- 13 Machine Learners
- 14 Python vs Scala
- 15 Kratt
- 16 Menial Work
- 17 Lack of Understanding
- 18 Spark
- 19 Tabriz
- 20 DataFrame vs DataSet
- 21 Scala as the defacto ML language
- 22 Problem with onboarding
- 23 How we assimilate the influx
- 24 Twitter
- 25 Hire a person
- 26 MOOCs
- 27 No spec by spec
- 28 When will it work
- 29 How does it feel
- 30 The point of Spark
- 31 Why Spark
- 32 Hyperparameter Tuning
- 33 Data Cleaning
- 34 ETL
- 35 Migration
- 36 Catching Errors
- 37 Scale
- 38 Picture
- 39 categorical variables
- 40 pipelines
- 41 pipeline approach
- 42 graphics staff
- 43 pros
- 44 disappointments
- 45 conclusion
- 46 thank you
