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ambassador blog draft #1269

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name: Marcel Ribeiro-Dantas
avatar: marcel.jpg
---

Scientist at [Institut Curie](https://intstitut-curie.org).
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151 changes: 151 additions & 0 deletions content/blog/2020-05-08-dvc-ambassador-program.md.md
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title: 'Join the DVC Ambassador Program!'
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date: 2020-05-08
description: |
We're launching our ambassador program for people all around the world to get involved in
the DVC community.
descriptionLong: |
We're launching our ambassador program for people all around the world to get involved in
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the DVC community.
picture: 2020-05-08/Ambassador_Header.png
author: marcel_rd
commentsUrl: https://discuss.dvc.org/t/new-video-reimagining-devops-for-machine-learning/341
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tags:
- Ambassador
- Volunteer
- Talks
- Meetup
- Outreach
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---

Software can be everywhere, but developers can’t - that’s why ambassadors, folks
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who do outreach and community building around projects they love, are a key part
of the open-source community. DVC is starting an ambassador program to help
people who are passionate about our mission get involved.

What is that mission, exactly? DVC is founded on the principle of engineering
solutions for making data science and machine learning rigorous and
reproducible. If this matters to you, too, you might be a good fit for our
ambassador program!

As an ambassador, you’ll act as a bridge between DVC in your community. There
are lots of ways to do this, big and small. For example:

- Write a blog post talking about how you use DVC in your projects
- What about creating a network of DVC users and data scientists in your town?
Even though we’re self-isolating now, you can still organize online meetups.
[We already did one!](https://tulu.la/events/dvc-virtual-meetup-2020-00032c).
We help cover costs to organize meetups.
- Do you want to talk about DVC at your office, or at a conference? We help
speakers develop talks, and we have some discretionary funds for travel on a
case-by-case basis.
- Want to develop a feature for DVC? We welcome contributions to the code base,
even if it’s your first pull request ever.

Being an ambassador means getting closer to the team in charge of DVC, but at
the same time, it means going farther to reach people outside the organization-
including people who don’t know about DVC yet, people who need some help getting
started, and people who are already excited about our mission and want to find
meaningful ways to pitch in.

It’s challenging, no doubt, but being an ambassador can be an amazing
experience! Before becoming DVC’s first official ambassador, I served as a
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[Fedora ambassador](https://fedoraproject.org/wiki/User:Mribeirodantas) for
several years. I got a lot out of it: I participated in lots of events, made
friends, and traveled. Every single time I’ve contributed to an open source
project, I got this nice feeling that it was all worth it. If you agree with the
core values of the project, a great relationship lies ahead :).

## About Iterative and DVC

DVC got started in 2017 as a personal project by Dmitry Petrov (on May 4,
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[we celebrated our 3rd birthday](https://dvc.org/blog/dvc-3-years-and-1-0-release)).
In 2018, Dmitry teamed up with his co-founder Ivan Shchenklein to incorporate
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Iterative.ai and grow the project. Currently, Iterative.ai’s flagship project is
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Data Version Control (DVC), an open source version control system for managing
complex workflows, datasets, and models. Development is ongoing in the core DVC
project as well as new ventures into
[MLOps and Continuous Integration & Delivery (CI/CD)](https://dvc.org/blog/reimagining-devops-video)
for data science. The team is small-and-mighty, with developers, engineers, and
data scientists on four continents. The open source community is a huge part of
all Iterative.ai projects; currently, DVC has more than
[5,000 stars on GitHub](https://github.com/iterative/dvc) and more than 100
individual contributors!

One of DVC’s main principles is adapting existing software engineering practices
to machine learning. For example, DVC is built around Git version control: in an
ML project using DVC, each experiment corresponds to a Git commit. When you
check out any commit, you’ll see the source code as it was when you made the
commit- as expected. But, you’ll also see your datasets as they were and the
exact pipeline of commands you ran in that experiment!

## How to become an ambassador

If you’re interested in becoming an ambassador, send us an email at [email protected]
with the subject line “I want to be an ambassador!” Please tell us:

- A little about yourself and your professional background
- Any outreach work you’ve done before
- What kind of ambassador activities you’d be most interested in participating
in

The program is structured to provide a lot of flexibility, so each ambassador
can do outreach in ways that are personally motivating and enjoyable. There are
a few guidelines:

- We ask for a one-year commitment
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- We ask ambassadors to contribute four activities per year, about once every
three months.
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- For your first contribution, we ask for a blog post- this way, we can
collaborate with you to help get all the technical details right. After that,
it’s up to you!

## Some ideas to get started

Our official ambassador program is just starting, but our community already has
a lot of folks making noise. Here are just a few contributions we admire- we
think they’re pretty cool inspirations for future projects.

### Blogs and tutorials

Shareable blogs are one of our most effective outreach strategies. They give
visibility to the author _and_ new ways to use DVC, so it's a win-win.

- [Remote training with GitLab-CI and DVC](https://blog.codecentric.de/en/2020/01/remote-training-gitlab-ci-dvc/),
by Mercel Mikl and Bert Besser (Bert has also organized a DVC meetup in
Berlin)
- [Creating a solid Data Science development environment](https://towardsdatascience.com/creating-a-solid-data-science-development-environment-60df14ce3a34),
by Gabriel dos Santos Goncalves
- [Continuous Delivery for Machine Learning](https://martinfowler.com/articles/cd4ml.html),
by Danilo Sato, Arif Wider, and Christoph Windheuser
- [Manage your Data Science Project in R](https://mribeirodantas.xyz/blog/index.php/2020/03/05/r-dvc-and-rmarkdown/)
was my first blog post about using DVC in an R project!

### Talks

Community members have presented at events like PyCon, PyData, and local
meetups.

- [Version control for data science](https://www.slideshare.net/AlessiaMarcolini/version-control-for-data-science),
by Alessia Marcolini @ PyCon DE & PyData Berlin
- [How to easily set up and version control your machine learning pipelines](https://www.youtube.com/watch?v=rUTlqpcmiQw),
by Sarah Diot-Girard & Stephanie Bracaloni @ PyData Amsterdam
- [ML models and dataset versioning](https://speakerdeck.com/kurianbenoy/ml-models-and-dataset-versioning),
by Kurian Benoy @ PyCon India

### Code contributions

Our GitHub repository has lots of open discussions about potential features- its
a goldmine for ways to pitch in. For example:

- [Helge Munk Jacobsen](https://github.com/elgehelge) took on an open issue in
our code base about supporting hyperparameter tracking with DVC and made a
pull request to add this feature.

- [Vera Sativa](https://github.com/verasativa/) added directory support to the
`dvc import-url` function- and she was our 100th contributor, so she won her
own
[DeeVee the Owl](https://dvc.org/static/78b685e283d679c8ebe518ea17520f6d/75999/odd_with_deevee.png).

If any of this sounds fun to you, please be in touch. We look forward to
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connecting with you!
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