Difference between revisions of "Feature Exploration/Learning"
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* The Passenger Screening Kaggle challenge [http://www.kaggle.com/c/passenger-screening-algorithm-challenge/discussion/45805 1st place solution] was won in part due to data preparation/generation. | * The Passenger Screening Kaggle challenge [http://www.kaggle.com/c/passenger-screening-algorithm-challenge/discussion/45805 1st place solution] was won in part due to data preparation/generation. | ||
* [http://www.kdnuggets.com/2018/10/notes-feature-preprocessing-what-why-how.html Notes on Feature Preprocessing: The What, the Why, and the How | Matthew Mayo - KDnuggets] | * [http://www.kdnuggets.com/2018/10/notes-feature-preprocessing-what-why-how.html Notes on Feature Preprocessing: The What, the Why, and the How | Matthew Mayo - KDnuggets] | ||
| + | * [[Self Learning Artificial Intelligence - AutoML & World Models]] | ||
Revision as of 09:19, 16 February 2019
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- Datasets
- Batch Norm(alization) & Standardization
- Data Preprocessing
- Hyperparameters
- Data Augmentation
- Visualization
- Master Data Management (MDM) / Feature Store / Data Lineage / Data Catalog
- Data Cleaning Challenge: .json, .txt and .xls | Rachael Tatman
- The Passenger Screening Kaggle challenge 1st place solution was won in part due to data preparation/generation.
- Notes on Feature Preprocessing: The What, the Why, and the How | Matthew Mayo - KDnuggets
- Self Learning Artificial Intelligence - AutoML & World Models
Sparse Coding - Feature extraction
