References
The following articles, blog posts, and videos were used as a resource during the preparation of this chapter. However, these are also important from the perspective of further reading.
- https://support.sas.com/resources/papers/proceedings14/SAS313-2014.pdf
- http://www.minicomplexity.org/pubs/1943-mcculloch-pitts-bmb.pdf
- http://psycnet.apa.org/psycinfo/1959-09865-001
- http://www.sascommunity.org/sugi/SUGI82/Sugi-82-121%20Sarle.pdf
- https://www.hakkalabs.co/articles/spark-mllib-making-practical-machine-learning-easy-and-scalable
- http://spark.apache.org/docs/latest/ml-pipeline.html
- http://www.slideshare.net/databricks/practical-machine-learning-pipelines-with-mllib
- https://databricks.com/blog/2015/01/07/ml-pipelines-a-new-high-level-api-for-mllib.html
- http://machinelearningmastery.com/discover-feature-engineering-how-to-engineer-features-and-how-to-get-good-at-it/
- http://www.haberdar.org/discrete-cosine-transform-tutorial.htm
- >http://stackoverflow.com/questions/17469835/one-hot-encoding-for...
