R Expands to Machine Learning and Deep Learning at ODSC East

(This article was first published on R-posts.com, and kindly contributed to R-bloggers)

For many, R is the go-to language when it comes to data analysis and predictive analytics. However many data scientists are also expanding their use of R to include machine learning and deep learning.

These are exciting new topics, and ODSC East — where thousands of data scientists will gather this year in Boston — has several speakers scheduled to lead trainings in R from April 30 to May 3.

Can’t make it to Boston? Sign up now to Livestream the conference in its entirety so as not to miss out on the latest methodologies and newest developments.

Some of the most anticipated talks this year at the conference include “Mapping Geographic Data in R” and “Modeling the tidyverse,” which will be further discussed, below. For a full list of speakers, click here.

Highlighted R-Specific Talks:

In “Machine Learning in R” Part 1 and Part 2, with Jared Lander of the Columbia Business School, you will learn everything ranging from the theoretical backing behind ML up through the nitty-gritty technical side of implementation.

Jared will also present “Introduction to R-Markdown in Shiny,” where he will cover everything from formatting and integrating R, to reactive expressions and outputs like text, tables, and plots. He will also give an “Intermediate R-Markdown in Shiny” presentation to go a bit deeper into the subject.

With everything Jared is presenting on, you definitely have quite a lot to work with for R and Shiny. Why not take it a step further and be able to communicate your findings? Alyssa Columbus of Pacific Life will present “Data Visualization with R Shiny,” where she will show you how to build simple yet robust Shiny applications and how to build data visualizations. You’ll learn how to use R to prepare data, run simple analyses, and display the results in Shiny web applications as you get hands-on experience creating effective and efficient data visualizations.

For many businesses, non-profits, educational institutions, and more, location is important in developing the best products, services, and messages. In “Data Visualization with R Shiny” with Joy Payton of the Children’s Hospital of Philadelphia, you will use R to take public data from various sources and combine them to find statistically interesting patterns and display them in static and dynamic, web-ready maps.

The “tidyverse” collects some of the most versatile R packages: ggplot2, dplyr, tidyr, readr, purrr, and tibble, all working in harmony to clean, process, model, and visualize data. In “Modeling in the tidyverse” author and creator of the Caret R package, Max Kuhn, Phd, will provide a concise overview of the system and will provide examples and context for implementation.

Factorization machines are a relatively new and powerful tool for modeling high-dimensional and sparse data. Most commonly they are used as recommender systems by modeling the relationship between users and items. Here, Jordan Bakerman, PhD and Robert Blanchard of SAS will present “Building Recommendation Engines and Deep Learning Models Using Python, R and SAS,” where you will use recurrent neural networks to analyze sequential data and improve the forecast performance of time series data, and use convolutional neural networks for image classification.

Connecting it All

R isn’t siloed language; new machine and deep learning packages are being added monthly and data scientists are finding new ways to utilize it in machine learning, deep learning, data visualization, and more. Attend ODSC East this April 30 to May 3 and learn all there is to know about the current state of R, and walk away with tangible experience!

Save 30% off ticket prices for a limited time when you use the code RBLOG10 today.

Register Here

More on ODSC:

ODSC East 2019  is one of the largest applied data science conferences in the world. Speakers include some of the core contributors to many open source tools, libraries, and languages. Attend ODSC East in Boston this April 30 to May 3 and learn the latest AI & data science topics, tools, and languages from some of the best and brightest minds in the field.

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