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R-Ladies Dec Tutorial: Scalable Machine Learning in R & Python with H20!
Thu 1 December 2016, 18:15 – 20:00 GMT
R-Ladies London, the UK chapter of the international R-Ladies Global network, invites you to our Decmber Tutorial! As a non-profit org promoting gender diversity in the R community, our events are always FREE to attend. To be notified of future events, join our official Meetup Group and follow us on Twitter @RLadiesLondon!
Timings: talk starts at 6.15pm, ends 8pm
Our speaker is Dr. Erin LeDell, fellow Co-founder of the R-Ladies Global community and an Organiser of R-Ladies San Francisco, who's stopping over in London to give this talk! She's a Statistician & Machine Learning Scientist at H2O.ai, the company that produces the open source machine learning platform, H2O. She's also the author of a handful of machine learning related software packages, including the h2oEnsemble!
The focus of this talk is scalable machine learning using the H2O R & Python packages. H2O is an open source, distributed machine learning platform designed for big data, with the added benefit that it's easy to use on a laptop (in addition to a multi-node Hadoop or Spark cluster). The core machine learning algorithms of H2O are implemented in high-performance Java, however, fully-featured APIs are available in R, Python, Scala, REST/JSON, and also through a web interface.
R & Python code with H2O machine learning code examples will be demo-ed live and are available on GitHub (https://github.com/h2oai/h2o-tutorials#r-tutorials) for attendees to follow along on their laptops.
Since H2O's algorithm implementations are distributed, this allows the software to scale to very large datasets that may not fit into RAM on a single machine. H2O currently features distributed implementations of Generalized Linear Models, Gradient Boosting Machines, Random Forest, Deep Neural Nets, dimensionality reduction methods (PCA, GLRM), clustering algorithms (K-means), anomaly detection methods, among others. The ability to create stacked ensembles, or "Super Learners", from a collection of supervised base learners is provided via the h2oEnsemble R package.
NOTE: the venue has NO public WiFi, only access for those with eduroam accounts. It's YOUR RESPONSIBILITY TO ACCESS THE REQUIRED MATERIALS BEFOREHAND.
Whilst fulfilling our commitment to promoting R amongst those identifying as female, all learners who comply with our community Code of Conduct are welcome to attend R-Ladies London. We are fully inclusive and respectful of queer and trans identities.
Code of Conduct: anyone who violates or has previously violated this community's Code of Conduct will be refused entry, expelled, and/or any other action deemed appropriate by the Organiser, regardless of event registration, meetup membership or other condition.