During the conference our Platinum and Gold sponsors will give presentations organised in a Sponsor Session. Below you may find their abstracts.
The sponsor presentations will take place Friday, July 3rd, from 10:15 to 12:00. The presenters will follow each other in the order below beginning with DataRobot and finishing with HP.
Ted Kwartler (max. 20 minutes)
In this presentation we will present the power of the DataRobot API, a programmatic access to a massively parallel modeling engine. The presentation will include use cases and examples.
Tareef Kawaf (max. 15 minutes)
Since the last useR! conference at UCLA, RStudio has been making investments in a variety of areas that make it easier for data scientists and analysts to create and share their analyses with the world. In today’s presentation we will give you a flavor for the work we have done and leave you with pointers so you can explore the items that are of deeper interest. We will provide a high level view of the various investments in the IDE, new R packages, enhancements to existing packages, and the newest options for enterprises deploying R and Shiny in production.
Venkatesh Sellapa (max. 15 minutes) [slides]
The world of R has collided with big data introducing the challenge: How can organizations analyze massive volumes of data working within memory limitations? In this session, you will learn how Teradata addresses this challenge with high speed, scalable R solutions that allows Global 1000 companies to tackle big data business problems. Do you want to work with innovative solutions? Join the Teradata team.
David Smith (max. 15 minutes) [slides]
In April this year, Revolution Analytics became a Microsoft company. In the announcement, Microsoft said it would “build R and Revolution’s technology into our data platform products so companies, developers and data scientists can use it across on-premises, hybrid cloud and Azure public cloud environments”. In this short talk I will share some progress that has been made at Microsoft on integrating R, and provide some details on what you can expect in the future.
Dan Putler (max. 10 minutes) [slides]
Organizations have an increasing amount of data that can be converted into information that offers the ability to make better decisions, find new opportunities, and improve efficiency. R is a critical advanced analytics tool that many organizations use to turn data into usable information. While the R language is comparatively easy to learn, it is still a traditional, written, computer programming language. Unfortunately, this fact alone limits the potential diffusion of R across most organizations, reducing its potential benefit to an organization. Alteryx is a platform for data blending and advanced analytics. Its objective is to empower a greater number of individuals across an organization to successfully accomplish these tasks, improving the overall performance of an organization. Alteryx uses R as a key element in powering much of its advanced analytics capabilities, in a much easier to approach interface. Alteryx itself is best viewed as both a data pipelining engine and a visual programming framework. In this talk, we introduce ourselves, highlight the benefits we provide our customers, particularly as it relates to R, and cover some of the things we do to help support the R community.
Lou Bajuk-Yorgan (max. 10 minutes) [slides]
R provides tremendous value to statisticians and data scientists; however, these users of R are often challenged to extend that value to the rest of their organization. TIBCO, through it's enterprise-class, alternative R interpreter, TIBCO Enterprise Runtime for R (TERR), helps R users share their analytics more widely. TERR draws upon our long history of developing S+, and is integrated into BI applications (through Spotfire), real-time environments (through TIBCO Streambase), and into 3rd party products (such as Lavastorm Analytics), helping R users serve a much wider audience within their organizations. TERR provides an embeddable, high-performance platform for R language analyses.
Amy Wang (max. 10 minutes) [slides]
H2O is a fast, scalable, open-source machine learning platform for building smarter applications. Customers like PayPal, Nielsen, Cisco and others choose H2O for accurate prediction scenarios and combinations of high volume data with multiple models. H2O's speed enables more iterations from a broad selection of algorithms, including GLM, Random Forest, GBM, and Deep Learning. H2O’s easy-to-use APIs allow users to immediately integrate models into R, Python, Spark, Excel or Tableau. The company’s customers have built powerful predictive engines for Recommendations, Customer Churn, Propensity to Buy, Dynamic Pricing and Fraud Detection for sectors including Insurance, Healthcare, Telecommunications, AdTech, Retail and Finance
Indrajit Roy (max. 10 minutes)
HP Distributed R is an open-source framework for large-scale machine learning, statistical analysis, and graph processing. It splits tasks among multiple nodes and supports your favorite statistical packages. We will discuss HP’s open source effort to make R scale and how you can help add more scalable algorithms to R. Come be part of it!