Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Please note that all times are shown in the time zone of the conference. The current conference time is: 26th Sept 2021, 07:20:11pm UTC

 
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Session Overview
Session
Tutorials - Track 4
Time:
Wednesday, 07/July/2021:
7:00am - 11:59pm


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Presentations
7:00am - 9:00am
ID: 306 / 4-Tut: 1
Tutorial
Topics: Web Applications (Shiny/Dash)
Keywords: Shiny, Modules, Code reuse, Software engineering, Reactivity

Structure your app: introduction to Shiny modules

Jonas Hagenberg

- Language: English

- Duration: 120

- N° Participants: 25

- Level: Intermediate

You communicate your results interactively with Shiny, maintain a dashboard or provide business logic, but the codebase of your app becomes too complex? Then modules are the right tool for you, they are the Shiny built-in solution to manage this complexity. Shiny modules allow you to break down your code into smaller building blocks that can be combined and reused.

In this tutorial I give an introduction into modules, its advantages over simple R functions and how existing functionality can be transferred to modules.

For an easy start, I cover common pitfalls needed to overcome for a productive use of modules:

- Passing reactive objects to modules

- Returning reactive values from the module to the calling environment

- Nesting modules

- Dynamically generating modules (including UI)

The contents of the tutorial are delivered by short lectures followed by hands-on coding sessions in break-out rooms. For this, you need a basic knowledge of reactive programming/Shiny.



9:00am - 10:30am
ID: 336 / 4-Tut: 2
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10:30am - 1:30pm
ID: 307 / 4-Tut: 3
Tutorial
Topics: Data mining / Machine learning / Deep Learning and AI, Interfaces with other programming languages

Getting started with torch (in French)

Sigrid Keydana, Daniel Falbel

- Language: English

- Duration: 180 mn

- N° Participants: 100

- Level: Intermediate

Torch (https://torch.mlverse.org/) is an open source machine learning framework based on PyTorch. Not requiring any Python dependencies, torch for R is at once a powerful computational engine with including GPU acceleration, a neural network library, and an ecosystem providing tools for, among others, image, text, and audio processing. This tutorial will provide a thorough introduction to torch basics: tensors, automatic differentiation, and neural network modules. Thereafter, we delve into two areas of special interest to R users: time series forecasting and numerical optimization. All sections will include time slots for practice.

Training materials will be available in an English version as well. Participants not speaking French, but who would like to join the training anyway, are welcome to ask questions in English in the chat.



1:30pm - 1:45pm
ID: 337 / 4-Tut: 4
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1:45pm - 2:45pm
ID: 308 / 4-Tut: 5
Tutorial
Topics: Data mining / Machine learning / Deep Learning and AI

Pinguinos en caja : tutorial interactivo de ciencia de datos con pinguinos - Español.

Maria Dermit, Susana Escobar

- Language: Spanish

- Duration: 60 mn

- N° Participants: 100

- Level: Intermediate

Pingüinos en Caja es un paquete learnr que cubre los temas del libro R para ciencia de datos y utiliza el conocido paquete de datos pinguinos para explorar los conceptos del libro.

El paquete contiene actualmente un tutorial para cada capítulo del libro y se presentará durante el taller. Además, los asistentes trabajarán en salas para grupos pequeños

módulos divididos por las secciones principales del libro (por ejemplo, Explorar, Wrangle, Programar, Modelar y Comunicar; 6 apartados en total) según sus objetivos de aprendizaje.

Las personas de la audiencia de este tutorial son estudiantes que quieran mejorar sus habilidades en ciencia de datos de forma interactiva y docentes que quieran acceder a recursos de aprendizaje adicionales similares a los Primers de Rstudio (https://rstudio.cloud/learn/primers). El tutorial tiene como objetivo ser interactivo y la instrucción entre pares entre los asistentes será dirigida para guiar el aprendizaje en las salas de grupos pequeños.



2:45pm - 3:00pm
ID: 338 / 4-Tut: 6
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3:00pm - 6:00pm
ID: 309 / 4-Tut: 7
Tutorial
Topics: Big / High dimensional data, R in production, Web Applications (Shiny/Dash)

Data Pipelines at scale with R and Kubernetes - Spanish

Frans van Dunné

- Language: Spanish

- Duration: 180

- N° Participants: 40

- Level: Advanced

"Many R users are confronted with larger and larger amounts of data that need to be processed. In this tutorial we will show you how to go to the next level by massively parallelizing your R code on a Kubernetes cluster. We will show you how to move your entire data pipeline to Kubernetes where each node in the pipeline consists of a container running R code. These containers can run with multiple cores, and then farmed out to tens or hundreds of these containers running in parallel.

Our experience has shown that this allows for massive speed gains, at relatively low cost when the kubernetes cluster is populated with ephemeral virtual machines (e.g. preemptible VM's on GCP - Spot instances on AWS). You need to have an interest in the more technical aspects of running R code, but only to a degree. We hope to dispel any fear that you might have that setting up a cluster is something that is very difficult. A key tool we will introduce is a tool to create data pipelines on kubernetes called Pachyderm (the open source version). The tutorial will be a combination of theory, break outs to run things hands on, regrouping to talk about experiences and then taking the next step. We will set up code examples in steps, so that if

one step di not work out, after regrouping the group can take off from the next starting point.



6:00pm - 6:15pm
ID: 339 / 4-Tut: 8
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6:15pm - 9:15pm
ID: 310 / 4-Tut: 9
Tutorial
Topics: Spatial analysis, Environmental sciences, Data visualisation

Datos espaciales a lo tidy - Español

Elio Campitelli, Paola Corrales

- Language: Spanish

- Duration: 180

- N° Participants: 40

- Level: Intermediate

En este tutorial vas a aprender a descargar, leer, analizar y visualizar datos espaciales grillados en R usando datos tidy. Va a ser un tutorial participativo con programación en vivo y ejercicios, bajo la idea de que puedas usar los datos para responder tus propias preguntas, escribiendo tu propio código.

Al final del taller vas a haber aprendido como:

- descargar datos meteorológicos y climáticos programáticamente desde R,

- leerlos en un formato tidy,

- computar estadísicas espaciales y temporales,

- graficar los resultados usando ggplot2 y extensiones.



 
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