[{"data":1,"prerenderedAt":309},["ShallowReactive",2],{"project-23759332":3},{"id":4,"name":5,"line":6,"line_source":7,"title":8,"url":9,"domain":10,"maker":11,"posted_at":12,"year":13,"points":14,"comments":15,"rank_in_year":16,"shown_in_year":17,"top":18,"tier":19,"category":20,"subcategory":21,"format":22,"keywords":23,"reception":29,"sentiment":30,"stance_mix":31,"scored_comments":36,"aspects":37,"strip":42,"post_text":45,"what":46,"said":95,"maker_in_thread":175,"shape":183,"grid":187,"attempts":272,"same_week":273,"maker_shows":35,"maker_hidden":302,"reader_version":303,"card":304},"23759332","Continuous Machine Learning","CI\u002FCD for Machine Learning Projects","title","Show HN: Continuous Machine Learning – CI\u002FCD for Machine Learning Projects","http:\u002F\u002Fcml.dev","cml.dev","rhythmvertigo",1594130348,2020,171,38,346,3028,12,"notable","dev_tools","ci\u002Fcd for machine learning","library",[24,25,26,27,28],"continuous integration","machine learning ci","github actions","gitlab ci","dvc","loved",0.34,{"positive":32,"neutral":33,"mixed":34,"critical":35},9,10,0,1,20,{"idea":38,"performance":40,"docs":41},{"positive":39,"critical":35},6,{"positive":34,"critical":34},{"positive":34,"critical":34},[34,43,34,44,34,44,44,44,43,34,44,34,34,43,43,43,44,34,34,44,44,44,34,35,34,34,43,34,34,43,34,43,34,43,34,44,34,34],5,3,null,{"problem":47,"audience":54,"pricing":45,"motivation":62,"time_to_build":45,"stack":69,"openness":92,"stage":93,"team_size":94},{"value":48,"source":49,"evidence":50},"Brings CI\u002FCD and human-readable metric reports to ML projects, which pass\u002Ffail tests alone do not cover","maker",[51],{"id":52,"by":11,"text":53},"23759339","Hi, I'm one of the project creators. Continuous Machine Learning (CML) is an open source project to help ML projects use CI\u002FCD with Github Actions and Gitlab CI…",{"value":55,"source":56,"evidence":57},"ML teams and data scientists using Git-based workflows","inferred",[58,59],{"id":52,"by":11,"text":53},{"id":60,"by":11,"text":61},"23760445","Yeah, we were seeing a lot of users organically asking about CI\u002FCD. DVC had to come first to address some of the data management issues, which seemed like the biggest hurdle to…",{"value":63,"source":49,"evidence":64},"Extend DevOps practices from software development to ML projects",[65,66],{"id":52,"by":11,"text":53},{"id":67,"by":11,"text":68},"23760464","Thanks for the kind words! DevOps has had profound results and we think culturally and technically, it's the right moment to push for those practices in ML.",[70,74,78,82,88],{"value":71,"source":49,"evidence":72},"GitHub Actions",[73],{"id":52,"by":11,"text":53},{"value":75,"source":49,"evidence":76},"GitLab CI",[77],{"id":52,"by":11,"text":53},{"value":79,"source":49,"evidence":80},"DVC",[81],{"id":52,"by":11,"text":53},{"value":83,"source":49,"evidence":84},"Docker",[85],{"id":86,"by":11,"text":87},"23760042","Thanks, and good questions! 1. Yes! Let me link some reports and example repos: - A basic classification problem with scikit learn:…",{"value":89,"source":49,"evidence":90},"Node.js npm package",[91],{"id":86,"by":11,"text":87},"open_source","unknown","company",{"praise":96,"objections":116,"requests":124,"questions":147,"alternatives":161},[97,109],{"value":98,"source":99,"evidence":100},"Useful bridge between DVC and CI systems","commenter",[101,105],{"id":102,"by":103,"text":104},"23759481","calebkaiser","This is really cool. We've been recommending DVC to our users for a long time, and this looks like a natural step forward for the Iterative ecosystem.",{"id":106,"by":107,"text":108},"23761906","rkaplan","Longtime DVC user here - this is going to be so helpful. We use DVC for all of our model and data versioning, but what's been missing is the ability to cleanly integrate that…",{"value":110,"source":99,"evidence":111},"Hashicorp-like approach for ML tooling",[112],{"id":113,"by":114,"text":115},"23760129","tnachen","Awesome to see a github native workflow for CI\u002FCD in the ML space! This team is closet I seen that's like Hashicorp for ML",[117],{"value":118,"source":99,"evidence":119},"Continuous deployment of ML models may be risky compared to software",[120],{"id":121,"by":122,"text":123},"23761935","bigfoot675","I think taking the approach of \"help[ing] your team make informed, data-driven decisions\" through generating reports is valuable here. In my opinion, it goes too far if we start…",[125,136],{"value":126,"source":99,"evidence":127},"Deeper GitLab merge request integration",[128,132],{"id":129,"by":130,"text":131},"23761726","sytse","Very cool to see this! I've added integrating CML closer into GitLab to our direction page with https:\u002F\u002Fgitlab.com\u002Fgitlab-com\u002Fwww-gitlab-com\u002F-\u002Fmerge_requests\u002F55367\u002Fdiffs If you…",{"id":133,"by":134,"text":135},"23762052","ishcheklein","Hey Sytse! Thanks for the kind words. We're very interested in a deep integration with Gitlab :) Can you share some examples of these security scan reports, please? Right now, we…",{"value":137,"source":99,"evidence":138},"Examples of real production use cases and documentation",[139,143],{"id":140,"by":141,"text":142},"23762262","m0sth8","CML looks really awesome. I've been on one of your online meetups. Are you planning to host more in the future? It would be great to learn real production use cases!",{"id":144,"by":145,"text":146},"23763623","gravypod","That's really cool. I might have to play around with this. Do you have any docs on what you do to deploy a model? Something I've been doing at work is dealing with the output of…",[148,154],{"value":149,"source":99,"evidence":150},"Support for on-prem GPU runners",[151],{"id":152,"by":145,"text":153},"23763527","This looks really amazing. Do you have any plans to support on-prem GPUs? If we had Gitlab runners with GPUs in them would this project pick it up and use those runners for…",{"value":155,"source":99,"evidence":156},"What happens when training fails and whether custom metrics are supported",[157],{"id":158,"by":159,"text":160},"23759912","toisanji","Very interesting, I've been looking for something like this to add to our ML pipeline. a few questions: 1) can we see examples of generated reports? 2) what happens if training…",[162,169],{"value":163,"source":99,"evidence":164},"Algorithmia CI\u002FCD GitHub Action",[165],{"id":166,"by":167,"text":168},"23765016","doppenhe","Deployment, inference and management can participate in this as well! Here is the missing part for a total e2e solution: https:\u002F\u002Fgithub.com\u002Fmarketplace\u002Factions\u002Falgorithmia-ci-cd…",{"value":170,"source":99,"evidence":171},"Cortex model deployment platform",[172],{"id":173,"by":103,"text":174},"23764381","Not to be too self-promotional here, but I'm a maintainer of Cortex, a model deployment platform that sounds like it might be useful: https:\u002F\u002Fgithub.com\u002Fcortexlabs\u002Fcortex With…",{"comments":176,"answered":44,"key":177},11,[178,179,180],{"id":52,"text":53},{"id":60,"text":61},{"id":181,"text":182},"23763578","Yep, it will work with your GPUs! You just set up self-hosted runners as usual https:\u002F\u002Fdocs.gitlab.com\u002Frunner\u002F GitHub & GitLab have both made it quite easy to use your own…",{"commenters":184,"max_depth":185,"maker_replies":176,"first_comment_mins":35,"lifespan_hours":186},18,7,166,[188,190,192,194,196,198,200,204,206,208,210,213,214,217,219,221,222,223,226,230,233,235,237,239,241,243,246,250,251,254,255,257,260,262,263,265,267,269],[52,34,34,189,11,35],"project\u002Fneutral\u002Fidea",[102,34,43,191,103,34],"project\u002Fpositive\u002Fidea",[60,34,34,193,11,35],"maker\u002Fneutral\u002Fidea",[152,34,44,195,145,34],"project\u002Fneutral\u002Fperformance",[181,34,34,197,11,35],"project\u002Fpositive\u002Fperformance",[144,34,44,199,145,34],"project\u002Fneutral\u002Fdocs",[201,34,44,202,203,34],"23764248","project\u002Fneutral\u002Fnone","dmpetrov",[205,34,44,202,145,34],"23764807",[207,34,43,191,134,34],"23765092",[173,34,34,209,103,34],"other\u002Fneutral\u002Fnone",[211,34,44,199,212,34],"23830989","davidortega",[166,34,34,209,167,34],[215,34,34,216,11,35],"23765206","project\u002Fpositive\u002Fnone",[218,34,43,216,212,34],"23830723",[220,35,43,191,134,34],"23760993",[129,35,43,191,130,34],[133,35,44,202,134,34],[224,35,34,209,225,34],"23762168","sam-white",[227,35,34,228,229,34],"23762280","other\u002Fneutral\u002Fdocs","stkerr",[231,35,44,232,130,34],"23762474","maker\u002Fneutral\u002Fnone",[234,35,44,232,134,34],"23762647",[158,236,44,202,159,34],2,[86,236,34,238,11,35],"maker\u002Fneutral\u002Fdocs",[121,44,35,240,122,34],"project\u002Fcritical\u002Fidea",[242,44,34,193,11,35],"23762236",[244,44,34,245,134,34],"23762247","commenter\u002Fneutral\u002Fidea",[247,248,43,191,249,34],"23760071",4,"tknaup",[67,248,34,193,11,35],[252,248,34,209,253,34],"23760562","obowersa",[113,43,43,191,114,34],[256,43,34,193,11,35],"23760423",[258,39,43,216,259,34],"23761550","ayanb9440",[261,39,34,232,11,35],"23761596",[106,185,43,216,107,34],[264,185,34,232,11,35],"23762241",[140,266,44,202,141,34],8,[268,266,34,232,11,35],"23762269",[270,266,34,271,141,34],"23762992","other\u002Fpositive\u002Fdocs",[],[274,278,283,287,292,297],{"id":275,"name":276,"points":277,"category":20},"23733926","USA.css",457,{"id":279,"name":280,"points":281,"category":282},"23760846","SheetUI",425,"web_saas",{"id":284,"name":285,"points":286,"category":282},"23771131","Runnaroo",380,{"id":288,"name":289,"points":290,"category":291},"23756964","I built a desktop radiation monitor with Raspberry Pi, brass and wood",364,"hardware",{"id":293,"name":294,"points":295,"category":296},"23762403","Map33.js",178,"languages",{"id":298,"name":299,"points":300,"category":301},"23723058","The Book of Minecraft Modding",150,"learning_science",false,"v2",{"id":305,"name":5,"line":6,"ai":302,"cat":20,"year":13,"points":14,"comments":15,"rec":29,"s":30,"top":18,"kw":306,"maker":11,"domain":10,"tier":19,"attempts":34,"strip":307,"url":9,"mix":308,"praise":98,"objection":118,"sub":21},23759332,[24,25,26,27,28],"05030333503005553003330100500505050300",[32,33,34,35],1793991012687]