talk-data.com

------ Welcome\, London R Users! ------ Welcome back! We can't wait to close the year with some great R talks :)

As before, the event will be brought to you by Datacove. We are a Data and Analytics Consultancy Team based in Brighton, working across Customer Analytics, Shiny and Reporting, Marketing Analytics and Process Automation.

We will be supported by the generous team at LSBU, organised by Valerio Ficcadenti from the Business School. Hosted by Jeremy Horne from Datacove.

------ Talk One ------ For our first talk, we are thrilled to be hosting Hannah Frick, Software Engineer at Posit.

As the author of Tidymodels, Hannah will be sharing 'What's New with Tidymodels?'. The `tidymodels` package in R is a collection of packages designed to streamline machine learning and modeling using a tidy and consistent framework. It integrates tools for model specification, data preprocessing, resampling, tuning, and evaluation. Key components include `parsnip` for fitting models with a unified syntax and `recipes` for flexible data preprocessing.

------ Talk Two ------ Datacove's own, Jeremy Horne, will be bringing us a quick but insightful talk to end the evening. As a man who has attended all 10 EARL Conferences - we're excited to hear his takeaways!

This talk will bring you a brief overview of the highlights and summaries from #EARLCONF 2024. Wanted to come but didn't make it? Look no further! The talk will feature Hadley Wickham, Author of the Tidyverse's insights on 'R in Production'. Takeaways from our workshops, plus, bonus tips from companies such as Vodafone, Natural England, Amazon, Microsoft and more.

------ General Information ------ Now, refreshments! Drinks and pizza will be served from 6pm. Talks will commence at 6:30pm/6:45pm and the event will conclude at 8:30pm.

The conversation will continue after the event at a local pub TBC – obviously!

Please feel free to register guests and spread the word. We look forward to seeing you all again!

Join us in partnership with R-Ladies NYC for an enlightening evening with Hadley Wickham as we explore the realm of "R in Production."

Agenda:

• 6:00 PM CET / 12:00 PM EDT Networking with R-Ladies Rome & NYC
• 7:00 PM CET / 1:00 PM EDT Dr. Hadley Wickham's Talk + Q&A

"This talk will discuss what it means to put R "in production". This isn't something you'll necessarily encounter early in your data science journey, but it's useful to have a strong mental model in place for when you inevitably face it. I'll discuss the three principles that I've found useful for distinguishing production for regular analyses:

Not just once: Successful data science projects are not a one-off, but will be run repeatedly for months or years. I'll discuss some of the challenges for creating R scripts and applications that run repeatedly, handle new data seamlessly, and adapt to evolving analytical requirements without constant manual intervention.

Not just my computer: the transition from development on your laptop (usually windows or mac) to a production environment (usually linux) introduces a number of challenges. Here, I'll discuss some strategies for making R code portable, how you can minimise pain when something inevitably goes wrong, and few unresolved auth challenges that we're currently working on.

Not just me: R is not just a tool for individual analysts but a platform for collaboration. I'll cover some of the best practices for writing readable, understandable code, and how you might go about sharing that code with your colleagues." - Hadley Wickham

In this engaging event, Hadley, renowned Chief Scientist at Positi PBC (former RStudio), will guide us into the practical applications and best practices for deploying R solutions in real-world production environments. From effective code structuring to ensuring scalability and reliability, Hadley will share invaluable insights and actionable tips for harnessing the full potential of R in production settings.

Whether you're a seasoned data scientist or just beginning your journey with R, this event promises to equip you with the knowledge and tools needed to successfully deploy R solutions and drive impactful outcomes in your organization.

Join us for an enlightening evening with Hadley Wickham as we explore the realm of "R in Production."

AGENDA:

• 12:00 PM EDT / 6:00 PM CET Networking with the R-Ladies
• 1:00 PM EDT / 7:00 PM CET Dr. Hadley Wickham's Talk + Q&A

IMPORTANT:

• Register for the event by filling out this form: https://forms.gle/dqRfdicoeWdAbJqu9
• You will receive a zoom link the morning of the event to the email address you provided when filling out the form.

"This talk will discuss what it means to put R "in production". This isn't something you'll necessarily encounter early in your data science journey, but it's useful to have a strong mental model in place for when you inevitably face it. I'll discuss the three principles that I've found useful for distinguishing production for regular analyses:

Not just once: Successful data science projects are not a one-off, but will be run repeatedly for months or years. I'll discuss some of the challenges for creating R scripts and applications that run repeatedly, handle new data seamlessly, and adapt to evolving analytical requirements without constant manual intervention.

Not just my computer: the transition from development on your laptop (usually windows or mac) to a production environment (usually linux) introduces a number of challenges. Here, I'll discuss some strategies for making R code portable, how you can minimise pain when something inevitably goes wrong, and few unresolved auth challenges that we're currently working on.

Not just me: R is not just a tool for individual analysts but a platform for collaboration. I'll cover some of the best practices for writing readable, understandable code, and how you might go about sharing that code with your colleagues." - Hadley Wickham

In this engaging event, Hadley, renowned Chief Scientist at Positi PBC (former RStudio), will guide us into the practical applications and best practices for deploying R solutions in real-world production environments. From effective code structuring to ensuring scalability and reliability, Hadley will share invaluable insights and actionable tips for harnessing the full potential of R in production settings.

Whether you're a seasoned data scientist or just beginning your journey with R, this event promises to equip you with the knowledge and tools needed to successfully deploy R solutions and drive impactful outcomes in your organization.

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

Abstract Hosted by Al Martin, VP, Data and AI Expert Services and Learning at IBM, Making Data Simple provides the latest thinking on big data, A.I., and the implications for the enterprise from a range of experts.

This week on Making Data Simple, we have Hadley Wickham is Chief Scientist at RStudio, and an Adjunct Professor of Statistics at the University of Auckland, Stanford University, and Rice University. He builds tools that make data science easier and faster, including the famous tidy verse packages for the R programming language. He was named a Fellow by the American Statistical Association for "pivotal contributions to statistical practice through innovative and pioneering research in statistical graphics and computing".

Show Notes 2:39 – Hadley talks about his journey  5:22 – Hadley talks about his American Statistical Association for "pivotal contributions to statistical practice" 8:00 – Tidy data concept 9:02 - How Hadley became interested in big data and R 10:12 – Python and R 12:30 – What Hadley is doing now 13:47 – Top 3 packages that help data scientists  17:47 – Hadley discusses his book  22:48 – Writing a book vs. code 29:40 – What language is going to take over 31:01 – What’s next for data 31:54 – What’s cool for Hadley 36:26 – Hadley’s Role model Hadley Wickham’s books Ggplot2 R for Data Science Advanced R R Packages Hadl Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

I'm joined by Wes McKinney (@wesmckinn) and Hadley Wickham (@hadleywickham) on this episode to discuss their joint project Feather. Feather is a file format for storing data frames along with some metadata, to help with interoperability between languages. At the time of recording, libraries are available for R and Python, making it easy for data scientists working in these languages to quickly and effectively share datasets and collaborate.

What is life but a series of questions? Does that question even make any sense? We'll never know, as this wasn't a question that got asked on this episode. Instead, Tom Miller, co-host of the Measured Direction podcast, joined us to give us a taste of the format of his show: user-submitted analytics questions asked and answered on the fly. What do you do when you lose a room of executives 15 minutes into your presentation? What does the future hold for digital analytics? Will we ever be able to measure the impact of TV? Who would win in a bar fight between Robocop and the podcast hosts? Find out the answers in a mere 45 minutes of audio (30 minutes if, like our guest, you listen at 1.5X speed).

People, places, and things mentioned in this episode include:

Measured Direction podcast Kevin Hillstrom Mine That Data Radio podcast Hadley Wickham Hadley Wickham on the Data Stories podcast R Adobe's Analysis Workspace Domo Jim Sterne Moe Kiss Clarivoy Comscore acquisition of Rentrak Google Adometry The Gary Angel episode of The Digital Analytics Power Hour

Turn your R code into packages that others can easily download and use. This practical book shows you how to bundle reusable R functions, sample data, and documentation together by applying author Hadley Wickham’s package development philosophy. In the process, you’ll work with devtools, roxygen, and testthat, a set of R packages that automate common development tasks. Devtools encapsulates best practices that Hadley has learned from years of working with this programming language. Ideal for developers, data scientists, and programmers with various backgrounds, this book starts you with the basics and shows you how to improve your package writing over time. You’ll learn to focus on what you want your package to do, rather than think about package structure. Learn about the most useful components of an R package, including vignettes and unit tests Automate anything you can, taking advantage of the years of development experience embodied in devtools Get tips on good style, such as organizing functions into files Streamline your development process with devtools Learn the best way to submit your package to the Comprehensive R Archive Network (CRAN) Learn from a well-respected member of the R community who created 30 R packages, including ggplot2, dplyr, and tidyr

In this insightful book, you'll learn from the best data practitioners in the field just how wide-ranging -- and beautiful -- working with data can be. Join 39 contributors as they explain how they developed simple and elegant solutions on projects ranging from the Mars lander to a Radiohead video. With Beautiful Data, you will: Explore the opportunities and challenges involved in working with the vast number of datasets made available by the Web Learn how to visualize trends in urban crime, using maps and data mashups Discover the challenges of designing a data processing system that works within the constraints of space travel Learn how crowdsourcing and transparency have combined to advance the state of drug research Understand how new data can automatically trigger alerts when it matches or overlaps pre-existing data Learn about the massive infrastructure required to create, capture, and process DNA data That's only small sample of what you'll find in Beautiful Data. For anyone who handles data, this is a truly fascinating book. Contributors include: Nathan Yau Jonathan Follett and Matt Holm J.M. Hughes Raghu Ramakrishnan, Brian Cooper, and Utkarsh Srivastava Jeff Hammerbacher Jason Dykes and Jo Wood Jeff Jonas and Lisa Sokol Jud Valeski Alon Halevy and Jayant Madhavan Aaron Koblin with Valdean Klump Michal Migurski Jeff Heer Coco Krumme Peter Norvig Matt Wood and Ben Blackburne Jean-Claude Bradley, Rajarshi Guha, Andrew Lang, Pierre Lindenbaum, Cameron Neylon, Antony Williams, and Egon Willighagen Lukas Biewald and Brendan O'Connor Hadley Wickham, Deborah Swayne, and David Poole Andrew Gelman, Jonathan P. Kastellec, and Yair Ghitza Toby Segaran