投稿時間:2021-12-08 18:44:02 RSSフィード2021-12-08 18:00 分まとめ(63件)

カテゴリー等	サイト名等	記事タイトル・トレンドワード等	リンクURL	頻出ワード・要約等/検索ボリューム	登録日
TECH	Engadget Japanese	Google、世界100万台に拡散のボットネット「Glupteba」を鎮圧。ロシア人運営者2人を提訴	https://japanese.engadget.com/google-disrupts-glupteba-botnet-085036043.html	glupteba	2021-12-08 08:50:36
TECH	Engadget Japanese	実売5000円以下でプレゼントにも最適！ MagSafe対応アクセサリーのおすすめはコチラ	https://japanese.engadget.com/magsafe-accessories-080559599.html	iphone	2021-12-08 08:05:59
ROBOT	ロボスタ	New Innovationsが非対面カフェのシステムを開発 渋谷スクランブルスクエア「ブルーボトルコーヒーPop Up Cafe」で採用	https://robotstart.info/2021/12/08/new-innovations-non-face-cafe.html	newinnovations	2021-12-08 08:54:54
ROBOT	ロボスタ	NVIDIAが「イチから分かる！Omniverse」を開催(1)　デジタルツインや3Dデザイン構築を支援する「Omniverse」とはなにか	https://robotstart.info/2021/12/08/nvidia-omniverse-meeting01.html	nvidia	2021-12-08 08:09:42
IT	ITmedia 総合記事一覧	[ITmedia News] Meta（旧Facebook)のメッセンジャー責任者が来年退社	https://www.itmedia.co.jp/news/articles/2112/08/news140.html	facebook	2021-12-08 17:20:00
IT	ITmedia 総合記事一覧	[ITmedia News] 前澤さん搭乗の宇宙船、打ち上げ成功　ISS到着は午後11時ごろ予定	https://www.itmedia.co.jp/news/articles/2112/08/news138.html	itmedia	2021-12-08 17:20:00
IT	ITmedia 総合記事一覧	[ITmedia ビジネスオンライン] 楽天銀行と楽天証券の口座連携「マネーブリッジ」、300万口座到達	https://www.itmedia.co.jp/business/articles/2112/08/news137.html	itmedia	2021-12-08 17:20:00
AWS	AWS Japan Blog	効率的なクラウドコスト管理戦略	https://aws.amazon.com/jp/blogs/news/strategy-for-efficient-cloud-cost-management-jp/		2021-12-08 08:40:57
AWS	AWS Japan Blog	廃棄物ゼロに至る道：ゴミ収集車両の走行ルートを最適化する	https://aws.amazon.com/jp/blogs/news/road-to-zero-waste-driving-efficiencies-sustainability-cloud-technology/	クラウド技術を利用することで、市の車両は単にゴミを回収するだけではなく、他にも様々なことができるようになりました。	2021-12-08 08:38:41
AWS	AWS Japan Blog	システム開発のモダナイズ、パート2 – 最初の一歩	https://aws.amazon.com/jp/blogs/news/modernizing-how-you-build-part-2-taking-the-first-step-jp/	システム開発のモダナイズ、パート最初の一歩AWSは、仕事に適したツールの選択、差別化につながらない作業のオフロード、ビルディングブロックの接続、すべての自動化を容易にするサービスを構築し続けています。	2021-12-08 08:09:52
AWS	AWS Japan Blog	効果的な e コマース技術チームを組織する方法	https://aws.amazon.com/jp/blogs/news/how-to-set-up-an-effective-ecommerce-tech-organization/	顧客中心主義とは、あなたが作ったすべての機能が顧客に価値を提供することを意味します。	2021-12-08 08:04:07
Google	Official Google Blog	This year, we searched for ways to stay healthy	https://blog.google/products/search/year-we-searched-ways-stay-healthy/	This year we searched for ways to stay healthyEvery day millions of people come to Google Search to ask important questions about their wellbeing The COVID pandemic drove even more concern for our health and the health of our loved ones and this year searches for ways to heal reached record highs We saw questions about vaccinations therapists body positivity and mental wellbeing to name a few Today we launched our annual Year in Search which takes a look back at the top trending searches of the year Here s a glimpse into some of the trending searches of a year we looked for ways to feel better and heal together Finding resources near meAcross the world people searched for information on COVID vaccinations and testing The top trending near me queries in were covid vaccine near me and covid testing near me To help people find credible timely testing and vaccine information we updated Google Search information panels and worked with national and international partners to help people get vaccinated and tested Learning how to helpHelping ourselves and our communities was a priority for many of us We asked questions about how to help others with anxiety and depression and we also looked for help with our own mental wellbeing Search interest for “therapists near me hit record highs in and the phrase why do I feel anxious for no reason also hit an all time high this year spiking more than In addition to providing mental health resources and helplines a quick Google Search also surfaces self assessments to help you learn more about mental health topics like depression anxiety PTSD and postpartum depression Evaluating information effectivelyIs it allergies or COVID A sinus infection or COVID Pfizer or Moderna As many of us searched for health related information online we wanted to know what we found was trustworthy Connecting people with critical timely and authoritative health information has been a crucial part of our role over the last year and our team is constantly working to find ways to help people everywhere find credible and actionable information to help manage their health To help people evaluate information online we launched a new tool called About This Result so you can learn more about the pages you see across a range of topics About This Result helps people evaluate the credibility of sources and decide which results are useful for them Search continues to be one of the first stops people make when making decisions big and small about their health ーand so much more To dive deeper into some of the other trending topics that defined visit yearinsearch google trends	2021-12-08 08:01:00
Google	Official Google Blog	Counting down 2021 with 21 Search trends	https://blog.google/products/search/counting-down-2021-21-search-trends/	Counting down with Search trendsEvery year the Search team takes a step back to look at the big picture to bring us Year in Search a fascinating exercise in analyzing global trends This year Search showed us how people prepared to leave quarantine fashion behind as well as what celebrities movies TV shows and moments fascinated us Here s a look at pop culture trends that really popped in according to Google Trends data This year we saw search interest for “Millennial and “Gen Z go neck and neck with interest in “Gen Z reaching an all time high and surpassing “Millennial in March So we decided to give the people what they want and looked at some of the trending Gen Z related searches The top trending Gen Z related search was for “Gen Z fashion This was followed by “Gen Z side part evidence of the oh so contentious hair debate Another top trending hair related search was for“are bangs in style Of course with all this interest in Gen Z it s only natural that people were searching “Gen Z slang On that subject…what exactly ischeugy You weren t the only one wondering It was the top trending definition search this year We also saw people searching for“Gen Z jeans Asking for a friend Are skinny jeans cheugy now In related searches Many of us asked “how to style straight leg jeans Red carpets also returned this year and “Megan Fox took the top trending red carpet look “Adam Sandler was this year s top trending source of celebrity outfit envy…so maybe some quarantine style is here to stay Have you ever binge watched a show so hard that you ended up wanting to dress like your favorite character Well you wouldn t be the only one This year s top trending fictional character outfit inspo came from “Outer Banks character Sarah Cameron Speaking of TV No yearly recap is complete without the top trending TV shows movies songs and celebrities The most searched TV Show was “Squid Game Kids of the s likely appreciate that “iCarly was the top trending TV Reboot Step aside Hamilton “In the Heights was the top trending drama movie The aptly titled “Halloween Kills stole the top spot among thriller movies And another reboot ー“Space Jam ーwas the top trending comedy movie For action movies “Black Widow was our winner Movies weren t the only kind of entertainment that hooked us though and there was one song in particular that drove pun intended many a search That s right “drivers license by Olivia Rodrigo Ball is life This year s top trending overall search was theNBA To round out this list we had to include a few trends that were going going gone…viral It s been nearly a year since Bernie Sanders took Washington D C by storm with his infamous winter wear but “Bernie Sanders mittens was the top trending meme for all of Ah yes in we were introduced to the eternal question Is it a Bones day or No Bones day Only Noodles knows And there was another kind of noodle we were very interested in You feta believe “tiktok pasta was the top trending recipe this year If you can t get enough of these trending queries be sure to check out our full Year in Search list and film for more	2021-12-08 08:01:00
Google	Official Google Blog	In 2021, the world searched for healing	https://blog.google/products/search/year-in-search-2021/	In the world searched for healingThis year searches for how to heal reached an all time high Across the world we were looking for ways to come back stronger We reflected on difficult times that continued to test our resolve We thought about those we lost asking “how to honor someone We looked inward searching for “how to take care of your mental health and asking the big questions like “how to be yourself and “what is my purpose We looked outward too thinking about how we could help rebuild and strengthen our communities We searched for how to make sustainable choices how to help Afghan refugees how to stop Asian hate and how to support people in need across the world from communities in India battling the pandemic to communities in Texas facing severe weather And we looked to move forward searching “how to make a come back As the world asked “how to be hopeful brought us hope This was the year that search interest for “covid vaccine officially surpassed interest in “covid testing Searches soared for “covid vaccine near me just as people eagerly asked when they could visit their family or eat in a restaurant again Like last year people continued to search for ways to stay connected and entertained at home “Squid Game took the top spot this year for searches for TV shows to watch But we also started to navigate a return to life outside the house wondering how we should go about ditching the sweatpants the top trending search for “how to style… was “how to style straight leg jeans As this year of comebacks comes to a close we re taking a closer look at trending topics across searches news people “how to s entertainment trends and more from across almost countries Search can help you find a world of information and what people search for can be a window into the world So join us in taking a closer look at this year s trending lists at yearinsearch google trends	2021-12-08 08:01:00
js	JavaScriptタグが付けられた新着投稿 - Qiita	Safari の contextmenu から<input type="file">をクリック	https://qiita.com/uhohaho/items/05bd94e54b4861b1b82f	「もしかして、contextmenuからのclickは左クリックにならないのではないか」と考えました。	2021-12-08 18:00:12
js	JavaScriptタグが付けられた新着投稿 - Qiita	PlayCanvas レンダリングコンポーネントの特徴を利用した簡単なキャラアニメーション制御	https://qiita.com/shujimuna1102/items/2092df2b8bcb8d211dbf	アニメーションの設定レンダリングコンポーネントへ移行したことで、アニメーションもStateGraphベースのものに変更されました。	2021-12-08 17:52:55
js	JavaScriptタグが付けられた新着投稿 - Qiita	Firebase Storageにてmetadataがうまく適応されない場合の対応	https://qiita.com/yoneapp/items/12524d4a403e59b840e1		2021-12-08 17:13:47
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	python,pandasで極座標データをデカルト座標のデータに直したい	https://teratail.com/questions/372878?rss=all	pythonpandasで極座標データをデカルト座標のデータに直したいpythonを用いて極座標をデカルト座標に直し、新規のcsvに保存したいです。	2021-12-08 17:48:50
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	viewを中央に配置できない	https://teratail.com/questions/372877?rss=all	viewを中央に配置できないswiftでコードで追加したviewをセンターに配置する方法を教えてください。	2021-12-08 17:48:20
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	コーナー検出を行った後にその特徴点を用いてマッチングを行いたい	https://teratail.com/questions/372876?rss=all	コーナー検出を行った後にその特徴点を用いてマッチングを行いたい前提・実現したいことステレオ画像においてコーナー検出を行い、コーナー検出で得た特徴点同士を特徴点マッチングを行ってマッチングさせたい。	2021-12-08 17:48:04
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	filter()内で、論理演算を行う方法	https://teratail.com/questions/372875?rss=all	具体的には、登録したすべてのお店に対して、閉店時間になるとお店の表示は消えるのですが、開店時間になる前から表示されてしまい困っています。	2021-12-08 17:47:46
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	Skyway 自動でルームに参加させたい	https://teratail.com/questions/372874?rss=all	Skyway自動でルームに参加させたい前提・実現したいことSkyWaynbspJSnbspSDKで、自動でルームに参加できるようしたい。	2021-12-08 17:45:25
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	unity GitHubを用いたゲームの公開	https://teratail.com/questions/372873?rss=all	unityGitHubを用いたゲームの公開unity初心者ですunityを使って作ったゲームをWeb上に公開したいと考えていますが、自分自身のサーバーを持っていませんGitHubを用いて公開していた例が記憶にあったので可能だと推測しているのですが、方法が調べても不明でした。	2021-12-08 17:38:20
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	AR表示させたときのオブジェクトの向きを180度変えたい	https://teratail.com/questions/372872?rss=all	AR表示させたときのオブジェクトの向きを度変えたいunityでARfoundationを用いてARアプリを作って、画像の上にオブジェクトを表示しているのですが、対象の画像を読み込んだ際にでてくるオブジェクトが自分が思うような向きを向いておらず正面ではなく後ろをむいた状態、今の状態からy軸を軸として度回転させた状態で表示したいです。	2021-12-08 17:29:09
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	JSで区間のあるデータを取出したい	https://teratail.com/questions/372871?rss=all	一日単位で取得することはできたのですが、過去日分をまとめて取得する方法が分からず困っています。	2021-12-08 17:23:24
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	階乗ループの回数を減らす方法を教えて下さい。	https://teratail.com/questions/372870?rss=all	つのノードに対して、すべてのノードでxyの差を求めているため、ループの回数がの階乗回回しています。	2021-12-08 17:15:21
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	ストロングパラメータで許可しているのに保存ができない	https://teratail.com/questions/372869?rss=all	ストロングパラメータで許可しているのに保存ができない前提・実現したいことRubyonnbspRailsを使って排便の記録をつけるアプリを作っています排便を投稿する機能を今作っているところですdeviseでユーザーを登録して他にテーブルが二つあり子ユーザーテーブルhumanと排便の記録テーブルpoopルーティングのネストさせています。	2021-12-08 17:14:00
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	開いているPDF内のリンクをクリックでPDFが自動添付されたメールアプリを起動する方法	https://teratail.com/questions/372868?rss=all	起動	2021-12-08 17:13:38
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	DBデータをlaravelに定義した定数で照会したい	https://teratail.com/questions/372867?rss=all	DBデータをlaravelに定義した定数で照会したいdbから取得とした番号を、laravel内に定義した定数を使用して値を取得したいと考えています。	2021-12-08 17:11:18
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	npm install --save electron でエラーが発生する	https://teratail.com/questions/372866?rss=all	npminstallsaveelectronでエラーが発生する前提・実現したいことElectronをインストールしたいのですが、エラーがでてしまいます。	2021-12-08 17:10:10
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	paiza ioで実行できるのにiMacでコンパイルするとコンパイルエラーが出る	https://teratail.com/questions/372865?rss=all	paizaioで実行できるのにiMacでコンパイルするとコンパイルエラーが出る下記の質問で挙げたプログラムをiMac環境でコンパイルしようとするとエラーがでます。	2021-12-08 17:09:48
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	画像の横にできる謎の空間を無くして、フィットさせたいです。	https://teratail.com/questions/372864?rss=all	画像の横にできる謎の空間を無くして、フィットさせたいです。	2021-12-08 17:04:01
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	[C#][LINQ] 単語を「あ、い、う、......、ん、A、B、......、W」の優先順位で並び替えたい。	https://teratail.com/questions/372863?rss=all	実現したいこと単語のリストをLINQを用いて、「あ、い、う、、ん、A、B、、W」の優先順位で順番に並び替えたいです。	2021-12-08 17:01:37
Linux	Ubuntuタグが付けられた新着投稿 - Qiita	Ubuntu で Go の最新版を使う	https://qiita.com/cointoss1973/items/23201d42f369932498b3	UbuntuでGoの最新版を使うUbuntuにてGoの最新版を使う手順です。	2021-12-08 17:31:42
golang	Goタグが付けられた新着投稿 - Qiita	Ubuntu で Go の最新版を使う	https://qiita.com/cointoss1973/items/23201d42f369932498b3	UbuntuでGoの最新版を使うUbuntuにてGoの最新版を使う手順です。	2021-12-08 17:31:42
技術ブログ	Mercari Engineering Blog	メルペイフロントエンドのテスト自動化方針	https://engineering.mercari.com/blog/entry/20211208-test-automation-policy-in-merpay-frontend/	hellip	2021-12-08 09:00:42
技術ブログ	Developers.IO	【現地セッションレポート】 Amazon SageMaker serverless inference (Preview) #AIM328 #reinvent	https://dev.classmethod.jp/articles/amazon-sagemaker-saverless-inference-preview/	amazonsagemasker	2021-12-08 08:42:32
海外TECH	MakeUseOf	Why Apple Named Toca Life World the Best iPhone App of 2021	https://www.makeuseof.com/why-toca-life-world-best-iphone-app-of-2021/	iphone	2021-12-08 08:27:49
海外TECH	DEV Community	Sideproject Update - Fluenticons v2	https://dev.to/fayaz/sideproject-update-fluenticons-v2-np	Sideproject Update Fluenticons vSo last February I had made a small weekend project and last month I released a version of it Fluenticons is an icon viewer for Microsoft fluent icons It has over open beautiful icons which you can use in your projects Fluenticons is now sponsored by Iconfinder sign up and get worth of credits via the banner in fluenticons What s new in v No more hacks I ve used actual SVG s now so I was able to add some new features like manipulating them You can copy snippets for SVGs Vue component React Component HTML Image You can download SVGs PNGs WEBP Vue component React Component now Manipulate colors to see how the icon looks More performant loads way too fast now Scores on Lighthouse Yay Was surprised to see the site loading in ms when I moved from vercel to cloudflare pages What s next Make an advanced editor like adding frames behind the icons Inspiration Bakery amp Iconscout s Icon Editor requires a lot a math which I am not good at Make a npm package for others to use the components in their own web projects probably looking a web component maybe like boxicons Tech stackNuxt jsTailwind Css Hosted on cloudflare pages	2021-12-08 08:46:18
海外TECH	DEV Community	Introducing Karpenter – An Open-Source High-Performance Kubernetes Cluster Autoscaler	https://dev.to/cloudtech/introducing-karpenter-an-open-source-high-performance-kubernetes-cluster-autoscaler-7g5	Introducing Karpenter An Open Source High Performance Kubernetes Cluster AutoscalerAt re Invent AWS announced the v release of Karpenter marking its open source Kubernetes node provisioning project as production ready With Karpenter Kubernetes users can now dynamically provision underlying compute nodes based on pod specifications more efficiently than the existing Kubernetes cluster autoscaler project Karpenter is an open source flexible high performance Kubernetes cluster autoscaler built with AWS It helps improve your application availability and cluster efficiency by rapidly launching right sized compute resources in response to changing application load Karpenter also provides just in time compute resources to meet your application s needs and will soon automatically optimize a cluster s compute resource footprint to reduce costs and improve performance Before Karpenter Kubernetes users needed to dynamically adjust the compute capacity of their clusters to support applications using Amazon EC Auto Scaling groups and the Kubernetes Cluster Autoscaler Nearly half of Kubernetes customers on AWS report that configuring cluster auto scaling using the Kubernetes Cluster Autoscaler is challenging and restrictive Kubernetes native cluster autoscaler is now production ready according to AWS So how does Karpenter work and how is it different than cluster autoscaler KarpenterIf you are familiar with GKE Autopilot s dynamic node provisioning process you can view Karpenter as an open source version of that tool designed to work with any Kubernetes cluster NOTE currently AWS is the only officially supported cloud provider Similar to GKE Autopilot Karpenter observes the pod specifications of unschedulable pods calculates the aggregate resource requests and sends a request to the underlying compute service e g Amazon EC with capacity needed to run all the pods Underneath the hood Karpenter defines a Custom Resource called Provisioner to specify the node provisioning configuration including instance size type topology e g zone architecture e g arm amd and lifecycle type e g spot on demand preemptible On the flip side Karpenter can also deprovision nodes when they are no longer needed This can be determined by node expiry config ttlSecondsUntilExpired or when the last workload running on Karpenter provisioned node is terminated Either of these two events triggers a finalization which cordons the nodes drains the pods terminates the underlying compute resource and deletes the node object This deprovisioning feature can also be used to keep the nodes up to date with the latest AMI as well Karpenter vs Cluster AutoscalerAt a cursory look Karpenter works similarly to the existing Kubernetes cluster autoscaler project After all cluster autoscaler is also cloud agnostic and can scale up or down based on pod resource requests Upon a closer look however Karpenter provides several advantages over cluster autoscaler Kubernetes native scaling Cluster autoscaler for AWS utilizes EC Auto Scaling groups to trigger scaling events Since ASGs were designed before Kubernetes this integration is clunky and slow For example managed node group users still can t configure it to scale nodegroups to making batch workload types more expensive to run on EKS No need to pre provision node groups Cluster autoscaler can only provision nodes based on specifications provided by node groups which require worker groups to have specific tags and work best with similar instance types This meant that if you wanted to run performance tests you needed to predefine a node group with beefier EC machine types for cluster autoscaler to trigger scaling events With Karpenter you can utilize all of AWS instance types on demand Since Karpenter manages each instance directly without node groups it is also much faster to request a new compute instance when capacity is unavailable Faster scheduling With cluster autoscaler pods rely on kube scheduler to create pods to new nodes once new resources become available Since Karpenter manages nodes directly it can immediately launch pods to new nodes without having to wait for the scheduler ConclusionWith Karpenter we can offload node provisioning autoscaling and upgrades and focus on running our applications Karpenter works with all kinds of Kubernetes applications but it performs particularly well for use cases that require rapid provisioning and deprovisioning large numbers of diverse compute resources quickly For example this includes batch jobs to train machine learning models run simulations or perform complex financial calculations Let me know your thoughts in the comment section about the new karpenter service And if you haven t yet make sure to follow me on below handles connect with me on LinkedInconnect with me on Twitter‍follow me on github️Do Checkout my blogs Like share and follow me for more content ltag user id follow action button background color important color fac important border color important Adit ModiFollow Cloud Engineer AWS Community Builder x AWS Certified x Azure Certified Author of Cloud Tech DailyDevOps amp BigDataJournal DEV moderator ‍Join our Cloud Tech Slack CommunityFollow us on Linkedin Twitter for latest news Take a Look at our Github Repos to know more about our projects ️Our Website	2021-12-08 08:25:29
海外TECH	DEV Community	MLOps journey with AWS - part 1 (helicopter view)	https://dev.to/aws-builders/mlops-journey-with-aws-part-1-helicopter-view-3gn1	MLOps journey with AWS part helicopter view in this series of posts we are going to start our journey into building MLops culture foundations and will see how to benefit from the help of AWS services for productizing our ml projects since this is the first article I want to set the foundations and also to give a full view of the tools or tech we need for our journey in building end to end CI CD CT pipelines for ML projects first let s take a closer look at a general ML Data projects life cycleas you can see there are main phases phase gathering ingestion extraction of data phase data exploring understanding cleaning transforming and pre processing why I put this in one phase is coz the more you understand the data the better you can pre process it and feature engineer it phase modeling training and validation phase serving according to above a simple ML project story team Ali is a data scientist jack is ml researcher mamon is ml engineer Ali gathered some data explored it and you did cleaning preprocessing and feature engineering on the data and delivered it to jack jack started to split data and do modeling and training and benchmarking now jack delivers a trained model with its artifact to mamon mamon validates the model builds the serving service and pushes the model to production now what is wrong with the above lifecycle the above is not a production ready solution here are some notes of why it is not a production ready is inefficient not scalable is not take into account data drift and no monitoring and clear visibility o the process from data to modeling what about the integration with the software team that will consume the ml service and use it a lot of manual delivery and cuts between each process but wait second what you mean by drifting In practice models often fail to adapt to changes in the environment or in data or some times for any reason we want to re train or re finetune or re deploy models to adapt to changes so we need to have monitor phase and re train pipeline and deploy pipeline with strategies so we can respond quickly to any kind of data or model drift for short I will give main types but there are other types Data drift can happen when there is a change in data distribution from the data that the model trained on and depending on that change or that new patterns there will be decreasing of model accuracy and performance another type of drift is concept drift that when the relationship between features and y the label is changedthat topic is very dependent on your use case the frequency depends on application nature and the trigger depends on the quality targe that if it can be measured without a human in the loop or it needs a human in the loop don t worry I will make a dedicated article for cover that topic with more details and with how to handle it using AWS in a few words is that there are new trends new patterns that happened we need our model o catchup with or the whole hypothesis have changed we need tore architecture the model or modelsso how MLops can help the above small team if the team want to scale and increase productivity while using best practices What is MLops it is an engineering culture and practice to unify ML system development ML Dev and ML system operation Ops by this we need to increase visibility and reduce manual steps and increase team collaboration and increase the speed of both rolling out and responding to new changes This means Automation and monitoring at all steps of ML system construction including integration testing releasing deployment and infrastructure management why MLops and not Devops Deference Between MLOps amp DevOps the nature of projects and teams involved in each one of the above MLOps DevOps make a need for extending the ideas the vision and tools of DevOps to be fit with ML Data projects the team in ML projects usually includes data scientists or ML researchers these members might not be experienced software engineers who can build production class services ML is experimental we need tracking and maintaining reproducibility while maximizing code reusability Testing an ML system need data validation trained model evaluation and validation ML models can have reduced performance not only coz of problems in coding but also due to drifting that mentioned above now what kind of extension need to be on CI CD to be fit with our need for MLOpsContinuous Integration CI extend the testing and validating code and components and add testing and validating data data schemas and models Continuous Delivery CD extending the service packaging and adding an ML training pipeline that should automatically deploy another service called model prediction service Continuous Training CT automatically retrains ML models for re deployment unique to ML systems property put in mind that re training triggers happen for reasons and are not automatic and in many cases need a human in the loop for the decision of such triggers so it case based approach but you must have a ready training pipeline with triggers Continuous Monitoring CM monitoring production data and model performance in terms of business metrics some goals we want to or try to achieve when applying MLops team collaboration and ease of tracking and re producing for code data models easy to share preprocessed data across teams projects or even moving between data channels like test and train good visibility and motioning in all the way from data to serving to even feedbacks from the end client of the final software easy to make decisions or triggering for any part such as triggering re training processing tools and tech to achive some or all of the above goals feature store here it will take care of automating some of Ali work preprocessing and feature engineering single source of truth to store retrieve remove track share discover and control access to features and you can use aws sagemaker feature store for that experiment tracking and model registry this will help jack in his experiments and will help mamon in reaching models while pushing to production and here we can use aws sagemaker model registry training pipeline no need for jack to re execute the training phase if a model decay happen a Trigger can start re training using the training pipeline defined by jack you can use aws sagemaker pipeline also you can use AWS lambda you can use TFX TorchX kubeflow serving pipeline base of production strategy this pipeline can help mamon from checking which model to validate and to re package and redeploy the serving services aws sagemaker pipeline also you can use aws lambda you can use TFX TorchX kubeflow data and model monitoring for drifting and decay with triggers here we can use aws sagemaker pipeline with model monitoring when we talk about pipeline we need orchestration and also we need automation aws sagemaker pipeline will manage that for you behind the scenes how we we can achieve all of the above in AWS a quick video	2021-12-08 08:16:10
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