投稿時間:2023-05-28 00:18:19 RSSフィード2023-05-28 00:00 分まとめ(19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
python	Pythonタグが付けられた新着投稿 - Qiita	【Paiza問題集】標準出力/出力幅を指定して出力	https://qiita.com/norma2627/items/d9db970f6c903ee12b52	paiza	2023-05-27 23:15:49
AWS	AWSタグが付けられた新着投稿 - Qiita	AWS Certified CLF, SAA, SOA, DVA 4冠しました！！	https://qiita.com/yuzu_juice/items/dfbfe9bf1bf188ad1a23	awscertifiedclfsaasoadva	2023-05-27 23:31:50
Docker	dockerタグが付けられた新着投稿 - Qiita	Docker + Flask + uWSGI + Nginxでwebアプリを作成する	https://qiita.com/engishoma/items/6fe4f0a5bf195ed271cd	dockerflaskuwsginginx	2023-05-27 23:46:27
技術ブログ	Developers.IO	評価エラーを導く要素と対策	https://dev.classmethod.jp/articles/evaluation-errors/	人事評価	2023-05-27 14:54:54
海外TECH	MakeUseOf	The Greening of Streaming: What Is It and Why Is It Necessary?	https://www.makeuseof.com/what-is-greening-of-streaming/	streaming	2023-05-27 14:45:18
海外TECH	MakeUseOf	How to Fix Z-Banding in 3D Prints	https://www.makeuseof.com/3d-printing-how-to-fix-z-banding/	horizontal	2023-05-27 14:30:18
海外TECH	MakeUseOf	How to Fix the System Image 0x80780119 Error on Windows	https://www.makeuseof.com/system-image-0x80780119-windows/	error	2023-05-27 14:15:18
海外TECH	MakeUseOf	How to Choose the Right Data Structure for Your Applications	https://www.makeuseof.com/how-to-choose-right-data-structure/	choice	2023-05-27 14:01:18
海外TECH	DEV Community	The Evolution and Impact of MLOps: understanding MLOps	https://dev.to/xakrume/the-evolution-and-impact-of-mlops-understanding-mlops-1dpo	The Evolution and Impact of MLOps understanding MLOpsMachine Learning Operations or MLOps is the missing bridge between machine learning data science and data engineering It has emerged as the link that unifies these functions more seamlessly than ever before So what is MLOps and why does it matter In this article we ll dive into the MLOps Hierarchy of Needs a fundamental concept that illustrates how MLOps supports enhances and optimizes the machine learning workflow within an organization DevOps The Foundation of MLOpsTo understand MLOps we must first understand the structure of this hierarchy which can be visualized as a pyramid At the base of this pyramid is DevOps the practice that enables continuous delivery and automated provisioning of environments Without a solid DevOps foundation there s no way an organization can successfully implement MLOps Key components of DevOps include infrastructure as code and a robust build system that allows services to be deployed in the staging environment and automatically propagated to production DevOps a combination of development and operations is a collaborative approach that streamlines the software development process It bridges the gap between development and operations teams facilitating continuous integration and delivery This methodology is essential for an organization to dive into MLOps Key components of DevOps include Infrastructure as Code IaC continuous delivery and a design based on a robust build system IaC enables automated provisioning of environments that can be integrated with your build system providing significant flexibility and reproducibility Similarly continuous delivery ensures that microservices are systematically updated in the staging environment and propagated to production increasing speed and efficiency Data Operations The Next LevelOnce the foundational level of DevOps is established the next step is to focus on data operations This involves setting up data management platforms such as Google BigQuery Databricks Snowflake or Amazon Athena These platforms facilitate serverless query and visualization workflows making data processing easier They also support data jobs and tasks to ensure efficient data operations MLOps Platforms Essential tools for machine learningThe third layer is the implementation of an MLOps platform This layer emphasizes the use of specialized tools rather than building everything from scratch which can take a lot of time away from core business objectives Building on the data operations layer it s time to integrate MLOps platforms These are specialized tools designed to streamline the machine learning process including feature stores model serving platforms and experiment tracking tools Feature stores store pre curated features for reuse while model serving platforms manage the deployment of ML models Experiment tracking tools help track various metrics and explanatory techniques and also monitor data drift allowing you to measure the impact of a model in production and observe how the underlying data changes over time They help monitor different metrics training techniques and data drift a concept that describes how the performance of an ML model can degrade over time as the underlying data changes The MLOps layer Workflow AutomationFinally we reach the top of the pyramid the MLOps layer itself Here the focus is on business value It s important to ensure that the machine learning models being created are delivering value to the organization This value can be tracked and quantified providing visibility that is useful for the health security and reputation of the organizations using the models Getting the problem right is also critical at this stage solving the wrong problem can lead to wasted resources and missed opportunities MLOps is not just about process it is also about transforming people and technology Successful MLOps implementation requires the participation of people from different levels and departments in an organization creating a culture of best practices There are several trends and predictions for MLOps in One key trend is the continued investment in machine learning driven by the rapid evolution of MLOps and the machine learning industry However the integration of MLOps continues to present challenges The onboarding and deployment of AI and ML algorithms can be complex requiring careful workload orchestration and server balancing A growing number of organizations are adopting tools like Metaflow open sourced by Netflix and AWS to design run and deploy their workflows at scale automatically versioning and tracking all experiments and data There is no consensus on a single MLOps tool or application and the growing number of libraries and packages in MLOps is expected to have a significant impact on enterprises ConclusionThe MLOps Hierarchy of Needs is a structured approach to implementing MLOps in an organization By starting with DevOps and gradually building up to data operations MLOps platforms and finally the MLOps layer itself organizations can streamline their ML workflows and maximize their business value The goal of MLOps isn t just about automation it s about driving efficiency and accelerating business outcomes Implementing MLOps can enable capabilities such as accurate inventory forecasting and the discovery of new patterns through unsupervised machine learning But remember the journey to MLOps is not a sprint it s a marathon It requires consistent effort constant learning and the right resources to successfully implement and manage MLOps in an organization	2023-05-27 14:00:58
Apple	AppleInsider - Frontpage News	Getting started with macOS Disk Utility: Resizing, snapshots, and journaling	https://appleinsider.com/inside/macos/tips/getting-started-with-macos-disk-utility-resizing-snapshots-and-journaling?utm_medium=rss	Getting started with macOS Disk Utility Resizing snapshots and journalingThere are a few less obvious features for managing and manipulating your storage devices in the macOS Disk Utility In the third part of our deep dive into Disk Utility here s how to find and use them In part and part of this series we looked at how to manage and manipulate storage devices and volumes on your Mac using Apple s Disk Utility app built in to macOS There are a few extra features you might want to be aware of so we ll cover those here Resizing disk images Read more	2023-05-27 14:47:14
海外TECH	CodeProject Latest Articles	Web Search Engine	https://www.codeproject.com/Articles/5319612/Web-Search-Engine	mining	2023-05-27 14:31:00
海外TECH	CodeProject Latest Articles	IntelliLink - An Alternative Windows Version to Online Link Managers	https://www.codeproject.com/Tips/839851/IntelliLink-An-Alternative-Windows-Version-to-Onli	intellilink	2023-05-27 14:22:00
海外TECH	CodeProject Latest Articles	IntelliPort - An Alternative Windows Version to the Famous HyperTerminal	https://www.codeproject.com/Articles/799126/IntelliPort-An-Alternative-Windows-Version-to-the	IntelliPort An Alternative Windows Version to the Famous HyperTerminalYou can use IntelliPort to transfer large files from a computer onto your portable computer using a serial port rather than going through the process of setting up your portable computer on a network	2023-05-27 14:20:00
海外TECH	CodeProject Latest Articles	IntelliTask - An Alternative Windows Version to the Famous Task Manager	https://www.codeproject.com/Articles/867009/IntelliTask-An-Alternative-Windows-Version-to-the	IntelliTask An Alternative Windows Version to the Famous Task ManagerTask Manager shows you the programs processes and services that are currently running on your computer You can use Task Manager to monitor your computer s performance or to close a program that is not responding	2023-05-27 14:18:00
海外TECH	CodeProject Latest Articles	IntelliFile	https://www.codeproject.com/Articles/5331868/IntelliFile	commander	2023-05-27 14:16:00
海外科学	NYT > Science	Ispace’s Japanese Moon Lander Crashed Because of Software Glitch	https://www.nytimes.com/2023/05/26/science/moon-crash-japan-ispace.html	Ispace s Japanese Moon Lander Crashed Because of Software GlitchIspace was aiming to become the first private company to land on the surface of the moon but lost contact with its robotic spacecraft in late April	2023-05-27 14:10:02
ニュース	BBC News - Home	TikToker Mizzy in court charged with breaching social media order	https://www.bbc.co.uk/news/uk-england-london-65732352?at_medium=RSS&at_campaign=KARANGA	media	2023-05-27 14:18:24
ニュース	BBC News - Home	Humza Yousaf accuses UK government of deposit return scheme sabotage	https://www.bbc.co.uk/news/uk-scotland-65731807?at_medium=RSS&at_campaign=KARANGA	scottish	2023-05-27 14:49:56
海外TECH	reddit	Red Bull floor	https://www.reddit.com/r/formula1/comments/13t8i7n/red_bull_floor/	Red Bull floor submitted by u KidTheBorax to r formula link comments	2023-05-27 14:10:15