Author: Open Data Science ODSC Team

R programmers are not necessary data scientists, but rather software engineers. We have an entirely new multitrack focus area that helps engineers learn AI skills – AI for Engineers. This focus area is designed specifically to help programmers get familiar with AI-driven software that utilizes deep learning and machine learning models to enable conversational AI, autonomous machines, machine vision, and other AI technologies that require serious engineering.

For example, some use R in reinforcement learning – a popular topic and arguably one of the best techniques for sequential decision making and control policies. At ODSC East, Leonardo De Marchi of Badoo will present “Introduction to Reinforcement Learning,” where he will go over the fundamentals of RL all the way to creating unique algorithms, and everything in between.

Well, what if you’re missing data? That will mess up your entire workflow – R or otherwise. In “Good, Fast, Cheap: How to do Data Science with Missing Data,” Matt Brems of General Assembly, you will start by visualizing missing data and identifying the three different types of missing data, which will allow you to see how they affect whether we should avoid, ignore, or account for the missing data. Matt will give you practical tips for working with missing data and recommendations for integrating it with your workflow.

How about getting some context? In “Intro to Technical Financial Evaluation with R” with Ted Kwartler of Liberty Mutual and Harvard Extension School, you will learn how to download and evaluate equities with the TTR (technical trading rules) package. You will evaluate an equity according to three basic indicators and introduce you to backtesting for more sophisticated analyses on your own.

There is a widespread belief that the twin modeling goals of prediction and explanation are in conflict. That is, if one desires superior predictive power, then by definition one must pay a price of having little insight into how the model made its predictions. In “Explaining XGBoost Models – Tools and Methods” with Brian Lucena, PhD, Consulting Data Scientist at Agentero  you will work hands-on using XGBoost with real-world data sets to demonstrate how to approach data sets with the twin goals of prediction and understanding in a manner such that improvements in one area yield improvements in the other.

What about securing your deep learning frameworks? In “Adversarial Attacks on Deep Neural Networks” with Sihem Romdhani, Software Engineer at Veeva Systems, you will answer questions such as how do adversarial attacks pose a real-world security threat? How can these attacks be performed? What are the different types of attacks? What are the different defense techniques so far and how to make a system more robust against adversarial attacks? Get these answers and more here.

Data science is an art. In “Data Science + Design Thinking: A Perfect Blend to Achieve the Best User Experience,” Michael Radwin, VP of Data Science at Intuit, will offer a recipe for how to apply design thinking to the development of AI/ML products. You will learn to go broad to go narrow, focusing on what matters most to customers, and how to get customers involved in the development process by running rapid experiments and quick prototypes.

Lastly, your data and hard work mean nothing if you don’t do anything with it – that’s why the term “data storytelling” is more important than ever. In “Data Storytelling: The Essential Data Science Skill,” Isaac Reyes, TedEx speaker and founder of DataSeer, will discuss some of the most important of data storytelling and visualization, such as what data to highlight, how to use colors to bring attention to the right numbers, the best charts for each situation, and more.

Ready to apply all of your R skills to the above situations? Learn more techniques, applications, and use cases at ODSC East 2019 in Boston this April 30 to May 3!

Save 10% off the public ticket price 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.

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.