From 450e401624ed2905ce576f38e854d79036872346 Mon Sep 17 00:00:00 2001 From: Elle Date: Fri, 24 Jul 2020 13:42:52 -0700 Subject: [PATCH] blog draft --- .../blog/2020-07-24-first-mlops-tutorial.md | 42 ++++++++++++++++++ .../uploads/images/2020-07-24/blog_header.png | Bin 0 -> 2493614 bytes .../uploads/images/2020-07-24/video_cover.png | Bin 0 -> 1048913 bytes 3 files changed, 42 insertions(+) create mode 100644 content/blog/2020-07-24-first-mlops-tutorial.md create mode 100644 static/uploads/images/2020-07-24/blog_header.png create mode 100644 static/uploads/images/2020-07-24/video_cover.png diff --git a/content/blog/2020-07-24-first-mlops-tutorial.md b/content/blog/2020-07-24-first-mlops-tutorial.md new file mode 100644 index 0000000000..be5492357b --- /dev/null +++ b/content/blog/2020-07-24-first-mlops-tutorial.md @@ -0,0 +1,42 @@ +--- +title: | + NEW VIDEO! 🎥 MLOps Tutorial #1: + Intro to continuous integration for ML +date: 2020-07-24 +description: | + A video tutorial abut using continuous integration in data + science and machine learning projects. This tutorial shows + how to use GitHub Actions and Continuous Machine Learning + (CML) to create your own automated model training and + evaluation system. +picture: 2020-07-24/blog_header.png +author: elle_obrien +commentsUrl: https://discuss.dvc.org/t/new-video-mlops-tutorial-1-intro-to-continuous-integration-for-ml/454 +tags: + - Continuous integration + - DevOps + - MLOps + - CML +--- + +Earlier this month, we launched [CML](https;//cml.dev), our latest open-source project in the MLOps space. We think it's a step towards establishing powerful DevOps practices (like continuous integration) as a regular fixture of machine learning and data science projects. But there are plenty of challenges ahead, and a big one is _literacy_. + +So many data scientists, like developers, are self-taught. Data science degrees have only recently emerged on the scene, which means if you polled a handful of senior-level data scientists, there'd almost certainly be no universal training or certificate among them. Moreover, there's still no widespread agreement about what it takes to be a data scientist: is it an engineering role with a little bit of Tensorflow sprinkled on top? A title for statisticians who can code? We're not expecting an easy resolution to these existential questions anytime soon. + +In the meantime, we're starting a video series to help data scientists curious about DevOps (and developers and engineeers curious about data science!) get started. Through hands-on coding examples and use cases, we want to give data science practitioners the fundamentals to explore, use, and influence MLOps. + +The first video in this series uses a lightweight and fairly popular data science problem- building a model to predict wine quality ratings- as a playground to introduce continuous integration. + +The tutorial covers: +- Using Git-flow in a data science project (making a feature branch and pull request) +- Creating your first GitHub Action to train and evaluate a model +- Using CML to generate visual reports in your pull request summarizing model performance + +It's now up on YouTube! + +https://youtu.be/9BgIDqAzfuA + +[Code for the project is available online](https://github.com/andronovhopf/wine) so you can follow along! We also recommend checking out the [CML docs](https://github.com/iterative/cml) for more details, tutorials, and use cases. + +If you have questions, the best way to get in touch is by leaving a comment on the blog, video, or our [Discord channel](https://discord.gg/bzA6uY7). And, we're especially interested to hear what use cases you'd like to see covered in future videos- tell us about your data science project and how you could imagine using continuous integration, and we might be able to create a video! + diff --git a/static/uploads/images/2020-07-24/blog_header.png b/static/uploads/images/2020-07-24/blog_header.png new file mode 100644 index 0000000000000000000000000000000000000000..a03aa70f0f5ba659b47e2028f82729c3397c46eb GIT binary patch literal 2493614 zcmV)7K*zs{P)wWi}d(PtSfBCPgW~UE+zS!vszt4|9h38&1O+LmhZPU!BU_;YmBEEdOY+vNMqXehJ?p8xu)X|6srtK}uzp3i)IvsoM+ zHx2&mVa?*TuP&O^)n(IMUp1@cRkOHxw{4^7^BJ#k_@B5R+}}+(r;m=^A2FWh&$-q6 zH_i3C*Ujqcg8hs3U)(-v7I#jX#qrJguZg*}x^Av7&YJ7<7tQM3s|N3YId^pDVRQ80 zS+ltFs99jXvA;LX{gFpN`&^zk*B9rU57+0va?Bpxd%{0_7tD_vm=iPSUw=K#HLA0K z>;K8Mwpfn`U!m9&FgC9)o7IPR&FcMWbN&8Jv$%D?IlB9(S=_$gERJq)Zp{B^y+ePj zmY#EXR9y4uhUOgScZ{PQ_FmkB>&6xD$NL`N$a_tG2aY4GMORJZXJ37I-{8;U<{i!F z8@IJ~%xWXeGqnBn+ZPi}Zey6uDV%#r3G|kfE25rK%?!s%H|IMGR 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