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"Official" November BARUG Meetup
Agenda: 6:30 - PM Pizza and Networking 7:00 - Announcements 7:05 - Anirudh Acharya - MXNet-R Lightning talk 7:20 - Tomas Nykodym - MLflow: Infrastructure for a Complete Machine Learning Life Cycle 7:45 - Javier Luraschi - Introduction to MLflow with R 8:10 - Norm Matloff - PolyanNA, a Novel, Prediction-Oriented R Package for Missing Values ############## Anirudh Acharya Introduction to the MXNet-R package Apache(Incubating) MXNet(https://github.com/apache/incubator-mxnet) is a modern open-source deep learning framework used to train, and deploy deep neural networks. It is scalable and supports multiple programming languages including C++, Python, Julia, R, Scala, and Perl. I will briefly introduce theMXNet-R package and run an example. ################ Tomas Nykodym MLflow: Infrastructure for a Complete Machine Learning Life Cycle ML development brings many new complexities beyond the traditional software development lifecycle including evaluating multiple algorithms, and parameters, setting up reproducible workflows, and integrating distinct systems into production models. In this talk, I will present MLflow, a new open source project from Databricks, that provides an open ML platform where organizations can use the ML libraries and development tools of their choice to reliably build and share ML applications. MLflow introduces simple abstractions to package reproducible projects, track results, and encapsulate models that can be used with many existing tools, accelerating the ML lifecycle for organizations of any size. Tomas Nykodym is an ML/AI Platform Engineer at Databricks working on MLflow. He spent his last 6 years working on cutting edge distributed machine learning projects at H2O.ai and Databricks. His professional interests include distributed computing, applied math and machine learning. ############### Javier Luraschi Introduction to MLflow with R This talk will teach you how to use MLflow from R to track model parameters and results, share models with non-R users and fine-tune models at scale. It will present the installation steps, common workflows and resources available for R. It will also demonstrate using MLflow tracking, projects and models directly from R as well as reusing R models in MLflow. Javier is a Software Engineer in RStudio working in R packages, most notably, sparklyr, cloudml, r2d3 and mlflow. ############## Norm Matloff PolyanNA, a Novel, Prediction-Oriented R Package for Missing Values Though there is a vast literature on techniques for handling missing values, almost all of it is focused on estimation, rather than on prediction. Here we present a novel approach developed specifically for use in prediction applications, implemented in an R package, 'polyanNA'. It can be used in both parametric and machine learning settings, and is very fast computationally. (Joint work with Pete Mohanty.)

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