Isabel Zimmerman
Senior Software Engineer
Hi there! I’m Isabel. I love creating things, whether that be making DIY crafts or open source tools. I’m keenly interested in making Python an easier and more fun place to do data science work.
I’ve spent time building Python packages like vetiver and pins as well as larger tools like the Positron IDE
. My favorite type of work tends to be at the intersection of practical, user-facing tools and data science. I’m part of the pyOpenSci community, serving as an editor, reviewer, and Editor-in-Chief emeritus (Winter 2024 rotation). I enjoy sharing my work through blog posts and conference talks. I’ve also compiled a more in-depth list of my work.
Coding is a place for me to be whimsical and creative, but I tend to also do a lot of non-computer hobbies! I’m an avid reader, amateur book-binder, constant doodler (I drew my entire landing page!), and am always teaching my old dog new tricks.
Software by Isabel Zimmerman#
Events attended by Isabel Zimmerman#
Posts and resources by Isabel Zimmerman#
How to use Positron’s GitHub integration | Isabella Velásquez & Libby Heeren | Data Science Lab
The Data Science Lab is a live weekly call. Register at pos.it/dslab! Discord invites go out each week on lives calls. We’d love to have you!
The Lab is an open, messy space for learning and asking questions. Think of it like pair coding with a friend or two. Learn something new, and share what you know to help others grow.
On this call, Libby Heeren and Isabella Velasquez walk through collaborating in Positron using the GitHub integrations and extensions. They show starting a project, protecting the main branch, opening and closing issues, creating and deleting branches, stashing and popping changes, resolving merge conflicts, opening and reviewing pull requests, and more.
Hosting crew from Posit: Libby Heeren, Isabella Velasquez, Isabel Zimmerman
Isabella’s Bluesky: https://bsky.app/profile/ivelasq3.bsky.social Libby’s Bluesky: https://bsky.app/profile/libbyheeren.bsky.social Isabella’s LinkedIn: https://www.linkedin.com/in/ivelasq/ Libby’s LinkedIn: https://www.linkedin.com/in/libbyheeren/
Resources mentioned in the video: Positron → https://positron.posit.co/ VS Code Source Control → https://code.visualstudio.com/docs/sourcecontrol/overview Positron “create issues” triggers (add your own, too!) → positron://settings/githubIssues.createIssueTriggers GitHub → https://github.com/ Linking a GitHub issue to a pull request → https://docs.github.com/en/issues/tracking-your-work-with-issues/using-issues/linking-a-pull-request-to-an-issue GitHub commands for PRs → https://docs.github.com/en/issues/tracking-your-work-with-issues/using-issues/linking-a-pull-request-to-an-issue Git → https://git-scm.com/ Quarto → https://quarto.org/ GitHub Pull Requests and Issues Extension → https://marketplace.visualstudio.com/items?itemName=GitHub.vscode-pull-request-github Azure DevOps → https://azure.microsoft.com/en-us/products/devops/ Happy Git with R → https://happygitwithr.com/ Software Carpentry Git → https://swcarpentry.github.io/git-novice/
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Thanks for hanging out with us!
Timestamps of Questions / Topics 00:00 Introduction 02:56 Creating a Quarto book project in Positron 05:54 Initializing a Git repository and publishing to GitHub 06:49 Creating a .gitignore file 08:00 “Do you have to create a GitHub account before starting this kind of project?” 11:53 Staging changes and making the initial commit 13:34 Adding a collaborator on GitHub 14:25 Setting up branch protection rules 15:25 “Was that push to GitHub the initialization of the GitHub repo?” “What if you already had a GitHub repo with that same name, would you get a warning in positron?” 18:50 Working with pull requests and issues directly in Positron 20:18 Cloning an existing repository 24:09 Undoing your last commit 24:41 Stashing staged changes 25:12 Creating a new branch 26:03 Applying changes by popping a stash 27:03 Creating a pull request 28:37 How to put your activity bar in Positron to the top 29:40 Reviewing and merging a pull request 32:46 Deleting local and remote branches 36:08 “Are there benefits to doing things within positron vs the GitHub UI?” 39:13 “Do you know how to delete a branch if it’s an older rogue branch?” 41:40 Using keywords to automatically create GitHub issues 43:24 “Is the functionality similar if you’re working with an internal organization like Azure DevOps version of Git?” 44:12 “What is the best way to get an orientation into the world of Git and GitHub?” 46:42 Pulling and synchronizing branches 49:01 How to resolve merge conflicts
Open source development practices | Isabel Zimmerman & Davis Vaughan | Data Science Hangout
ADD THE DATA SCIENCE HANGOUT TO YOUR CALENDAR HERE: https://pos.it/dsh - All are welcome! We’d love to see you!
We were recently joined by Isabel Zimmerman and Davis Vaughan, Software Engineers at Posit, to chat about the life of an open source developer, strategies for navigating complex codebases, and how to leverage AI in data science workflows. Plus, NERDY BOOKS!
In this Hangout, we explore the differences between maintaining established ecosystems like the Tidyverse as well as building new tools like the Positron IDE. Davis and Isabel (and sometimes Libby ) share practical advice for developers, such as the utility of AI for writing tests and “rubber ducking”, and their various approaches to writing accessible documentation that bridges the expert-novice gap.
Resources mentioned in the video and zoom chat: Positron IDE → https://posit.co/positron/ Air (R formatter) → https://posit-dev.github.io/air/ Python Packages Book (free) → https://py-pkgs.org/ R Packages Book (free) → https://r-pkgs.org/ DeepWiki (AI tool mentioned for docs) → https://deepwiki.com/tidyverse/vroom
If you didn’t join live, one great discussion you missed from the zoom chat was about Brandon Sanderson’s Cosmere books and the debate between starting with Mistborn vs. The Stormlight Archive. Are you a Cosmere fan?! Which book did you start with? (Libby started with Elantris years before picking up Mistborn Era 1 book 1, but she’d now recommend maybe starting with Warbreaker!)
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Thanks for hanging out with us!
Timestamps: 00:00 Introduction 04:41 “What does a day in the life of an open source dev look like?” 09:43 “What got you into building your own R packages?” 13:00 “Personal tips for working with code bases you’re not familiar with?” 16:35 “How much of what you build is in R/Python vs. lower-level languages?” 19:57 “Does Air work inside code chunks in Positron?” 20:12 “Changing the Python Quarto formatter in Positron without an extension” 22:56 “What do your side projects look like?” 26:40 “How do you approach writing documentation?” 30:55 “What interesting trends in data science are you noticing?” 33:38 “How do you leverage AI in your work?” 37:30 “What are the hexes on Davis’s back wall?” 38:50 “What career advice would you give to someone in a similar position?” 43:45 “How can I be more resilient when things go wrong?” 47:59 “Do you have keyboard preferences?” 49:25 “What is the best way to report bugs in packages?” 50:56 “Open source dev work vs. in-house dev work” 51:50 “Tips for getting started with Positron”
Exploring Positron settings | Isabel Zimmerman & Davis Vaughan | Data Science Lab
The Data Science Lab is a live weekly call. Register at pos.it/dslab! Discord invites go out each week on lives calls. We’d love to have you!
The Lab is an open, messy space for learning and asking questions. Think of it like pair coding with a friend or two. Learn something new, and share what you know to help others grow.
On this call, Libby Heeren is joined by Posit engineers Isabel Zimmerman and Davis Vaughan as they share some of their favorite settings in Positron, a super customizable data science IDE. Come laugh with us as we can’t seem to figure out that VSCode calls rainbow parentheses “bracket pair colorization”
Hosting crew from Posit: Libby Heeren, Isabella Velasquez, Daniel Chen, Isabel Zimmerman, Davis Vaughan
Resources from the hosts and chat: Install Positron: https://positron.posit.co/ Positron docs on keyboard shortcuts: https://positron.posit.co/keyboard-shortcuts.html Nathan Jeffery’s “click to open a .RDS file” keybinding: https://nathan-jeffery.netlify.app/blog/2025-08-26-read-rds-positron/ Positron R pipe setting (paste in browser and it’ll open in Positron): positron://settings/positron.r.pipe One of Dan Chen’s faves, the native tab feature in VSCode + Positron: https://lucasprag.com/posts/underrated-vscode-feature-native-tabs/ The list of RStudio keybindings that you get when you turn on RStudio keybindings in Positron: https://positron.posit.co/migrate-rstudio-keybindings.html Indent rainbow extension: https://open-vsx.org/extension/oderwat/indent-rainbow Rainbow brackets setting (paste in browser and it’ll open in Positron): positron://settings/editor.bracketPairColorization.enabled Setting hierarchy (User vs Workspace settings) in Positron: https://code.visualstudio.com/docs/configure/settings#_settings-precedence Rainbow CSV extension (not by Posit): https://marketplace.visualstudio.com/items?itemName=mechatroner.rainbow-csv Positron +1ePositron, an extension pack for dev and data science, by Garrick Aden-Buie: https://open-vsx.org/extension/grrrck/positron-plus-1-e Publishing from VS Code or Positron: https://docs.posit.co/connect/user/publishing-positron-vscode/ Posit Connect Cloud plans: https://connect.posit.cloud/plans Enter Folder extension that Libby mentions: https://open-vsx.org/extension/xiangda/enter-folder Catppuccin themes (shared by Rory Lawless, and now some of Libby’s favorites!): https://open-vsx.org/extension/Catppuccin/catppuccin-vsc
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Thanks for learning with us!
Timestamps 00:00 Introduction 00:42 Guest Introductions: Isabel and Davis 02:41 Positron Settings overview 04:11 How to enable “Format on Save” 04:34 “How do I open settings in JSON or UI?” 05:10 Auto Save on focus change 08:26 Enabling RStudio key bindings 09:28 “Why doesn’t the cursor move with code edits?” 12:18 User vs. Workspace settings 14:34 Creating and using Profiles 16:13 “Can I use the magrittr pipe with Control+Shift+M?” 17:23 Searching and managing keyboard shortcuts 19:42 Creating custom code snippets 21:31 The Indent Rainbow extension 24:04 Enabling rainbow parenthesis/brackets 25:08 Managing Python and R interpreters 26:32 Rearranging and hiding UI panes 28:04 Rainbow CSV and favorite extensions 29:26 Using the Enter Folder extension 31:05 Understanding the setting hierarchy 32:48 Adding symbols to Quick Open search 36:00 “Is there a way to shift focus using keyboard shortcuts?” 38:04 Modifying keybindings JSON for specific languages 39:20 “How do you find trustworthy extensions?” 43:11 “How can I publish to shinyapps.io from Positron?” 44:03 Deploying with Posit Publisher and Connect Cloud 48:32 Customizing themes with RainGlow extension 50:36 “Is there an Import Data Set wizard in Positron?” 53:01 Conclusion and community resources
IDE-ntity Crisis: Choosing the Right Tool for Me (Isabel Zimmerman, Posit) | posit::conf(2025)
IDE-ntity Crisis: Choosing the Right Tool for Me
Speaker(s): Isabel Zimmerman
Abstract:
Data practitioners have more IDE choices than ever, but not all are built for the same purpose. JupyterLab prioritizes a notebook-first experience, while VS Code focuses on software engineering with extensible features. Others, like Positron, are designed specifically for data scientists, streamlining workflows and boosting productivity.
Understanding these trade-offs helps you find the best fit. By the end of the session, you’ll have a clear framework for choosing the right IDE for your data science and analytics tasks. posit::conf(2025) Subscribe to posit::conf updates: https://posit.co/about/subscription-management/
TidyTuesday + Posit | PydyTuesday | Weekly Community Python Data Project
Posit software engineer Isabel Zimmerman discusses the TidyTuesday project and the Posit PydyTuesday Initiative. Learn how to participate in weekly TidyTuesday projects, watch Isabel explore Central Park squirrel data, and discover how to deploy your work to Posit Connect Cloud. Find her code here: https://github.com/isabelizimm/pydy-tuesday
Check out these repositories to join the TidyTuesday and the Posit PydyTuesday Initiative:
TidyTuesday repo with datasets: https://github.com/rfordatascience/tidytuesday Posit PydyTuesday repo: https://github.com/posit-dev/python-tidytuesday
Learn more about Quarto and Connect Cloud:
Quarto website: https://quarto.org/ Posit Connect Cloud: https://connect.posit.cloud/ Other videos in this Posit PydyTuesday playlist: https://www.youtube.com/playlist?list=PL9HYL-VRX0oSDQjicFMLIIdcLv5NuvDp9
#pythoncontent
Isabel Zimmerman - End-to-end data science with the Positron IDE | PyData NYC 2024
The process of data science is inherently iterative, requiring constant inspection and visualization of data. Positron is a new, next generation integrated development environment (IDE) built to facilitate exploratory data analysis, reproducible authoring, and publishing data artifacts. This talk will discuss the motivation behind creating Positron and demonstrate the features that support these iterative data science workflows.
PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.
PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.
00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details.
Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps
Introducing Positron, a new data science IDE - posit conf 2024
Positron is a next-generation data science IDE that is newly available to the community for early beta testing. This new IDE is an extensible tool built to facilitate exploratory data analysis, reproducible authoring, and publishing data artifacts. Positron currently supports these data workflows in either or both Python and R and is designed with a forward-looking architecture that can support other data science languages in the future. In this session, learn from the team-building Positron about how and why it is designed the way it is, what will feel familiar or new coming from other IDEs, and whether it might be a good fit for your own work.
Talk by Julia Silge, Isabel Zimmerman, Tom Mock, Jonathan McPherson, Lionel Henry, Davis Vaughan, and Jenny Bryan
Slide deck 1: https://speakerdeck.com/juliasilge/introducing-positron Slide deck 6: https://speakerdeck.com/jennybc/positron-for-r-and-rstudio-users
R-Ladies Rome (English) - Extending the data science workflow: {vetiver} and {pins}
In this video, Isabel Zimmerman goes through the fundamental aspects of machine learning operations (MLOps) tasks, bridging the gap between data analysis and model deployment. While data practitioners excel in data analysis and model development, there’s often a significant gap in understanding tasks beyond the conventional data science workflow.
You’ll explore crucial MLOps concepts, such as deploying models as API endpoints and monitoring model decay, while leveraging the powerful capabilities of the vetiver and pins packages.
Material:
- presentation: https://www.isabelizimm.me/talk-extending-ds-workflow-rladies/
- RStudioConf2022 talk: https://www.isabelizimm.me/talks/rstudioconf2022/
- Vetiver website: https://vetiver.rstudio.com/
0:00 Welcome & R-Ladies Rome Chapter Introduction 0:04:45 Slido Pools 0:10:15 Talk Intro 0:10:56 Isalbel’s Talk 0:47:53 Hands-on session 1:02:20 Q&A
Have a look at our WebSite for more insights about our events: https://rladiesrome.quarto.pub/website/talks/
R-Ladies Rome(English) - Extending the data science workflow: {vetiver} and {pins}- Isabel Zimmerman
In this video, Isabel Zimmerman goes through the fundamental aspects of machine learning operations (MLOps) tasks, bridging the gap between data analysis and model deployment. While data practitioners excel in data analysis and model development, there’s often a significant gap in understanding tasks beyond the conventional data science workflow.
You’ll explore crucial MLOps concepts, such as deploying models as API endpoints and monitoring model decay, while leveraging the powerful capabilities of the vetiver and pins packages.
Material:
- presentation: https://www.isabelizimm.me/talk-extending-ds-workflow-rladies/
- RStudioConf2022 talk: https://www.isabelizimm.me/talks/rstudioconf2022/
- Vetiver website: https://vetiver.rstudio.com/
0:00 Welcome & R-Ladies Rome Chapter Introduction 0:04:45 Slido Pools 0:10:15 Talk Intro 0:10:56 Isalbel’s Talk 0:47:53 Hands-on session 1:02:20 Q&A
Have a look at our WebSite for more insights about our events: https://rladiesrome.quarto.pub/website/talks/
Thanks, I Made It with Quartodoc - posit::conf(2023)
Presented by Isabel Zimmerman
When Python package developers create documentation, they typically must choose between mostly auto-generated docs or writing all the docs by hand. This is problematic since effective documentation has a mix of function references, high-level context, examples, and other content.
Quartodoc is a new documentation system that automatically generates Python function references within Quarto websites. This talk will discuss pkgdown’s success in the R ecosystem and how those wins can be replicated in Python with quartodoc examples. Listeners will walk away knowing more about what makes documentation delightful (or painful), when to use quartodoc, and how to use this tool to make docs for a Python package.
Presented at Posit Conference, between Sept 19-20 2023, Learn more at posit.co/conference.#
Talk Track: Data science with Python. Session Code: TALK-1139
Live Q&A: August 30th at 11:30 ET | Pins Workflow Demo Q&A Session
**IF YOU ARE HERE FIRST, PLEASE JOIN US IN THE DEMO ROOM AT 11 ET ON AUGUST 30TH - https://youtu.be/t8A-ysXinpE?feature=shared **
The Q&A portion will begin at 11:30 ET in this YouTube Room and the demo should automatically bring you over here.
Thanks so much for joining us!
- Rachael
Please join Ryan Johnson, Isabel Zimmerman, and Rachael Dempsey here for live Q&A following the end-to-end workflow demo on pins on August 30th.
If you end up here first, here’s the link to the demo room: https://youtu.be/t8A-ysXinpE?feature=shared
Please use the YouTube Chat for Q&A or feel free to ask questions anonymously here: pos.it/demo-questions
If you’d like to add future end-to-end workflow demos to your calendar you can use this link: pos.it/team-demo
Follow-up links:
- Demo recording will be here: https://youtu.be/t8A-ysXinpE?feature=shared
- Posit Team: https://posit.co/products/enterprise/team/
- Talk to us directly: https://posit.co/schedule-a-call/?booking_calendar__c=RST_YT_Demo
- Posit Team demo resources: pos.it/demo-resources
Thanks for joining us!
Building an MLOps strategy from the ground up - Isabel Zimmerman, RStudio PBC | Crunch 2022
This talk was recorded at Crunch Conference 2022. Isabel from RStudio PBC spoke about building an MLOps strategy from the ground up.
“By the end of this talk, people will understand what the term MLOps entails, different options for deployment, and when different methods work best.”
The event was organized by Crafthub.
You can watch the rest of the conference talks on our channel.
If you are interested in more speakers, tickets and details of the conference, check out our website: https://crunchconf.com/ If you are interested in more events from our company: https://crafthub.events/
Isabel Zimmerman - Practical MLOps for better models | PyData Global 2022
Machine learning operations (MLOps) are often synonymous with large and complex applications, but many MLOps practices help practitioners build better models, regardless of the size. This talk shares best practices for operationalizing a model and practical examples using the open-source MLOps framework vetiver to version, share, deploy, and monitor models.
PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.
PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.
00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details.
Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps
Isabel Zimmerman - Holistic MLOps for better science | PyData NYC 2022
Machine learning operations (MLOps) are often synonymous with large and complex applications, but many MLOps practices help practitioners build better models, regardless of the size. This talk shares best practices for operationalizing a model and practical examples using the open-source MLOps framework vetiver to version, share, deploy, and monitor models.
PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.
PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.
00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details.
Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps
MLOps with vetiver in Python and R | Led by Julia Silge & Isabel Zimmerman
Many data scientists understand what goes into training a machine learning model, but creating a strategy to deploy and maintain that model can be daunting. In this meetup, learn what MLOps is, what principles can be used to create a practical MLOps strategy, and what kinds of tasks and components are involved. See how to get started with vetiver, a framework for MLOps tasks in R and Python that provides fluent tooling to version, deploy, and monitor your models.
Blog Post with Q&A: https://www.rstudio.com/blog/vetiver-answering-your-questions/
For folks interested in seeing what data artifacts look like on Connect, we have these for R: ⬢ Versioned model object: https://colorado.rstudio.com/rsc/seattle-housing-pin/ ⬢ Deployed API: https://colorado.rstudio.com/rsc/seattle-housing/ ⬢ Monitoring dashboard: https://colorado.rstudio.com/rsc/seattle-housing-dashboard/ ⬢ Create a custom yardstick metric: https://juliasilge.com/blog/nyc-airbnb/ ⬢ End point used in the demo: https://colorado.rstudio.com/rsc/scooby
Our team’s reading list (mentioned in the meetup)
Books: ⬢ Designing Machine Learning Systems by Chip Huyen: https://www.oreilly.com/library/view/designing-machine-learning/9781098107956/
Articles: ⬢ “Machine Learning Operations (MLOps): Overview, Definition, and Architecture” by Kreuzberger et al: https://arxiv.org/abs/2205.02302 ⬢ “From Concept Drift to Model Degradation: An Overview on Performance-Aware Drift Detectors” by Bayram et al: https://arxiv.org/abs/2203.11070 ⬢ “Towards Observability for Production Machine Learning Pipelines” by Shankar et al: https://arxiv.org/pdf/2108.13557.pdf ⬢ “The ML Test Score: A Rubric for ML Production Readiness and Technical Debt Reduction” by Breck et al: https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/aad9f93b86b7addfea4c419b9100c6cdd26cacea.pdf
Web content: ⬢ How ML Breaks: A Decade of Outages for One Large ML Pipeline by Papasian and Underwood: https://www.youtube.com/watch?v=hBMHohkRgAA ⬢ MLOps Principles by INNOQ: https://ml-ops.org/content/mlops-principles ⬢ Google’s Practitioners Guide to MLOps by Salama et al: https://services.google.com/fh/files/misc/practitioners_guide_to_mlops_whitepaper.pdf ⬢ Gently Down the Stream by Mitch Seymour: https://www.gentlydownthe.stream/
Speaker bios: Julia Silge is a software engineer at RStudio focusing on open source MLOps tools, as well as an author and international keynote speaker. Julia loves making beautiful charts, Jane Austen, and her two cats.
Isabel Zimmerman is also a software engineer on the open source team at RStudio, where she works on building MLOps frameworks. When she’s not geeking out over new data science techniques, she can be found hanging out with her dog or watching Marvel movies
Isabel Zimmerman – Explaining model explainability
Machine learning doesn’t have the same objectives as its users. While models look to optimize a function using the given data, humans look to gain insight into their problems. At best, these two objectives align; at worst, machine learning models make the front page of the news for unintended, but astonishing bias. Model explainability algorithms allow data scientists to understand not only what the model outcome is, but why it is being made. This talk will explain what model explainability is, who should care, and show participants how/when to use multiple types of explainability algorithms.
This session shows the usefulness of a variety of algorithms, but also discusses the limitations. Told from a data scientist’s point of view, this session provides a use case scenario exposing unintended bias using healthcare data. The audience will learn: the basics of model explainability, why this is a relevant issue, how model explainability offers insight into unintended bias, and know how to deploy explainability algorithms in Python with alibi, the open-source library from Seldon.
Speaker: Isabel Zimmerman – https://2021.berlinbuzzwords.de/member/isabel-zimmerman
More: https://2021.berlinbuzzwords.de/session/explaining-model-explainability