Draft of October Heartbeat (#1858)

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content/blog/2020-10-12-october-20-dvc-heartbeat.md

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+---
+title: October '20 Heartbeat
+date: 2020-10-12
+description: |
+  This month, hear about our international talks, 
+  new video docs on our YouTube channel, 
+  and the best tutorials from our community.
+descriptionLong: |
+  This month, hear about our international talks, 
+  new video docs on our YouTube channel, 
+  and the best tutorials from our community.
+picture: 2020-10-12/cover.png
+pictureComment:
+  Double DeeVee! One of these birds is on a layover before heading to Germany.
+author: elle_obrien
+commentsUrl: https://discuss.dvc.org/t/october-20-heartbeat/527
+tags:
+  - Heartbeat
+  - CML
+  - DVC
+  - Tutorial
+  - Conference
+  - Meetup
+  - YouTube
+---
+
+## News
+
+### Paweł gets ready to speak at Poland's largest data science meeting
+
+DVC developer Paweł Redzyński (he's written a lot of the code behind
+`dvc plots`) is giving at talk at the [Data Science Summit](https://dssconf.pl/)
+in Poland! The virtual meeting is on October 16, but talks are available for
+streaming on demand up to a week before. Paweł's talk is part of the DataOps &
+Development track, where he'll be sharing about CML and GitHub Actions (note
+that it'll be delivered in English).
+
+[![](/uploads/images/2020-10-12/dss.png)](https://dssconf.pl)
+
+### Dmitry talks at Data Engineering Melbourne
+
+CEO
+[Dmitry Petrov dropped into the Data Engineering Melbourne meetup](https://www.meetup.com/Data-Engineering-Melbourne/events/267033998/)
+to talk about Data Versioning and DataOps! He spoke about the differences
+between end-to-end platforms and ecosystems of tools, and how this distinction
+informs the development of software like DVC and CML (hint: we picked tools over
+platforms).
+
+Keep an eye on this meetup, which is now accessible to folks on all continents
+thanks to the magic of the internet :)
+
+<external-link
+href="https://www.meetup.com/Data-Engineering-Melbourne/"
+title="Data Engineering Melbourne"
+description="Dmitry Petrov presents on DataOps and versioning."
+link="meetup.com"
+image="/uploads/images/2020-10-12/Meetup_Logo.png"/>
+
+### Elle has talks at PyCon India and PyData Global
+
+Last week I gave a talk about CML at
+[PyCon India](https://in.pycon.org/cfp/2020/proposals/how-to-make-continuous-integration-work-with-machine-learning~avK5b/),
+and have another one coming up at
+[PyData Global](https://global.pydata.org/talks/devops-for-science-using-continuous-integration-for-rigorous-and-reproducible-analysis)
+this November 11-15.
+
+<external-link
+href="https://global.pydata.org/talks/devops-for-science-using-continuous-integration-for-rigorous-and-reproducible-analysis"
+title="DevOps for science: using continuous integration for rigorous and reproducible analysis"
+description="PyData Global"
+link="https://global.pydata.org"
+image="/uploads/images/2020-10-12/pydata.png"/>
+
+PyData Global has a fantastic lineup of talks spanning science and engineering,
+so please consider joining!
+
+### DVC at DataFest
+
+DVC Ambassador Mikhail Rozhkov co-hosted the Machine Learning REPA
+(Reproducibility, Experiments and Pipelines Automation) track of
+[DataFest 2020](https://datafest.ru/), and DVC showed up in full force! There
+were talks from Dmitry, ambassador Marcel Ribeiro-Dantas, and myself about all
+aspects of MLOps and automation.
+
+DataFest is over (until next year, anyway), but
+[visit the ML-REPA community](http://ml-repa.ru/en#about) for ongoing content
+and opportunities for networking.
+
+### New videos
+
+Since the summer, we've been building our
+[YouTube channel](https://www.youtube.com/channel/UC37rp97Go-xIX3aNFVHhXfQ).
+It's going great- we've gotten more than 18,000 views in the last few months and
+1,500 subscribers!
+
+Our latest video in the
+[MLOps Tutorials](https://www.youtube.com/playlist?list=PL7WG7YrwYcnDBDuCkFbcyjnZQrdskFsBz)
+series introduced using GitHub Actions for model testing- instead of training a
+model in continuous integration, the idea is to train locally and "check-in"
+your favorite model for testing in a standardized environment. This approach
+lets you completely control the environment, infrastructure, and code used to
+evaluate your model, and save the run in a place that's easy to share (GitHub!).
+
+https://youtu.be/bSXUJRnQPPo
+
+We'll be going deeper into the art and craft of testing ML models in the next
+few weeks, so stay tuned. Another big initative is adding videos to our docs:
+since video seems like a popular format for a lot of learners, we're working to
+supplement our official docs with embedded videos. Check out our first
+installment on the
+[Getting Started with Data Versioning](https://dvc.org/doc/start/data-versioning).
+
+https://youtu.be/kLKBcPonMYw
+
+## From the community
+
+Our community makes some amazing tutorials. Here are a few on our radar:
+
+Data scientist and full-stack developer
+[Ashutosh Hathidara](https://github.com/ashutosh1919) shared an end-to-end
+machine learning project made with DVC and CML... and released it in video form!
+It's a neat setup and a nice model for folks to study.
+
+https://youtu.be/H1VBsK7XiKs
+
+Another detailed and easy-to-follow tutorial, with a similarly impressive scope,
+appared on [Heise Online](https://www.heise.de/). This project puts together
+DVC, Cortex, and ONNX to develop and deploy a model trained on the Fashion MNIST
+dataset (note: the article is in German, and I read it with Chrome's English
+translation).
+
+<external-link
+href="https://www.heise.de/hintergrund/Verwaltung-und-Inbetriebnahme-von-ML-Modellen-4911723.html"
+title="Managing and commissioning ML models"
+description="Tools like DVC and Cortex, which are designed for the operationalization of AI projects, are intended to help developers deploy models in production."
+link="https://heise.de"
+image="/uploads/images/2020-10-12/heise.png"/>
+
+You'll also want to check out [anno.ai](https://www.anno.ai/)'s tutorial about
+managing large datasets with DVC and S3 storage- it's detailed, but also a
+quick-start guide informed by the team's practical experience.
+
+<external-link
+href="https://medium.com/@anno.ai/mlops-and-data-managing-large-ml-datasets-with-dvc-and-s3-part-1-d5b8f2fb8280"
+title="MLOps and Data: Managing Large ML Datasets with DVC and S3 (Part 1)"
+description="A quick start guide to version control for machine learning data"
+link="medium.com/@anno.ai"
+image="/uploads/images/2020-10-12/legos.jpg"/>
+
+Data scientist and mathematician [Khuyen Tran](https://twitter.com/KhuyenTran16)
+blogged about why and how to start using DVC- and her tutorial includes Google
+Drive remote storage, a feature we're especially excited about. Check it out and
+follow along with her code examples!
+
+<external-link
+href="https://towardsdatascience.com/introduction-to-dvc-data-version-control-tool-for-machine-learning-projects-7cb49c229fe0"
+title="Introduction to DVC: Data Version Control Tool for Machine Learning Projects"
+description="Just like Git, but with Data!"
+link="medium.com"
+image="/uploads/images/2020-10-12/khuyen_tran.jpg"/>
+
+And to end on a thoughtful note... have you seen this thread by ML Engineer
+[Shreya Shankar](https://twitter.com/sh_reya)? She beautifully summarizes many
+of the ideas and technical challenges our community thinks about every day. Read
+and reflect!
+
+https://twitter.com/sh_reya/status/1314338372073263112