Tips and tricks for treating learning rate as a hyperparameter, and using visualizations to see what’s really going on.
Siddha graduated from Carnegie Mellon University with a Master's in Computational Data Science. Her work ranges from Visual Question Answering to Generative Adversarial Networks to gathering insights from CERN's petabyte scale data, and she has been published at top-tier conferences like CVPR. She is a frequent speaker at the Strata Data Conference and the Artificial Intelligence Conference, and she advises the Data Lab at NASA. When not working, you might catch her hiking! Visit Siddha's website at http://sidgan.me/siddhaganju.
Crunching CERN’s colossal data with scalable analytics
Apache Spark eyed as potential framework for big data analysis at one of the world’s most prominent nuclear research organizations.