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Doing your first Kaggle (Python for Big Data sets)
The document discusses a Kaggle tutorial by Lee Trawick focused on using Python for handling big data sets. It covers key topics such as loading data efficiently, dealing with memory management, and techniques for joining large tables. The presentation highlights examples and challenges faced when working with Kaggle competitions.
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Doing your first Kaggle (Python for Big Data sets)
- 1. Doing Your First Kaggle- Python for Big Data Sets Lee Trawick, ASA #datapopup
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- 4. How is thisrelevant?
- 5. Tell me againhow this is relevant?
- 6. Pokemon vs BigData Name! That! Pokemon! Hadoop Cloudera Bulbasour Mongo Talend Qubole Statwing Magikarp Flink Impala
- 7. It’s easy tosubmit to Kaggle.
- 8. Download someone’s codeand submit.
- 9. We’re on theleaderboard!
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- 12. First, I loadthe data.
- 13. How they loadthe data.
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- 15. Other ways tosave memory Delete objects when you’re done with them Specifying data types on every new column. Not just for loading files
- 16. My approach tothe “One Vector Problem”
- 17. Kaggle solution tothe “One Vector Problem”
- 18. The map() trickto joining large tables
- 19. Kaggle Solution -3 Key Things
- 20. Gameshow…Will! That! Work?! Loopingthrough big tables
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- 24. It’s the samecode
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