DVC AI
製品情報
レビュー
アナリティクス
エンベデッド
代替案
DVC AI 製品情報
DVC AIとは何ですか？
MLデータ管理、実験トラッキング、パイプラインの自動化のためのツールのスイート。
DVC AIの使い方は？
1. データとML実験のバージョン管理を行います。2. どのクラウドでも計算リソースを自動化します。3. ML実験をトラッキング・管理します。
DVC AIのコア機能
億を超えるファイルの処理
カスタム埋め込み
自動ラベル付け
バイアスの軽減
類似ファイルの削除
バージョン管理と共有
Gitを真理の唯一のソースとして使用
DVC AIの使用例
#1
データの前処理と管理
#2
実験のトラッキング
#3
MLモデルのバージョン管理
#4
パイプラインの自動化
DVC AIのFAQ
DVC AIとは何ですか？
DVC AIの主な機能は何ですか？
DVC AIの使用例は何ですか？
DVC AIの使用方法は？
DVC AI Discord
DVC AI の Discord は次のとおりです: https://discord.com/invite/dvwXA2N。 Discord メッセージの詳細については、ここ (/ja/discord/dvwxa2n) をクリックしてください。
DVC AI サポートメール、カスタマーサービス連絡先、返金連絡先など
さらに連絡するには、お問い合わせページ (https://dvc.ai/#learn_more) にアクセスしてください。
DVC AI の価格
DVC AI 価格リンク: https://dvc.ai/pricing
DVC AI のYoutube
DVC AI Youtubeリンク: https://www.youtube.com/channel/UC37rp97Go-xIX3aNFVHhXfQ
DVC AI のLinkedin
DVC AI Linkedinリンク: https://www.linkedin.com/company/iterative-ai/
DVC AI のTwitter
DVC AI Twitterリンク: https://twitter.com/DVCorg
DVC AI のGithub
DVC AI Githubリンク: https://github.com/iterative
DVC AI レビュー (0)
5 点中 5 点
DVC AI の分析
DVC AI 埋め込みを起動する
ウェブサイトバッジを使用して、Toolify Launchに対するコミュニティからのサポートを促進しましょう。ホームページやフッターに簡単に埋め込むことができます。
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埋め込みコードをコピーする
インストール方法
ソーシャルリスニング
Data Versioning in Generative AI: A Pathway to Cost Effective ML
This talk was presented at the 2023 MLOps World and Generative AI World Summit. Dmity Petrov shares on his learnings over 5 years of creating and maintaining DVC and how we can now tackle the management of unstructured Generative AI data in a cost-effective way. Talk Abstract: For 5 years we have been building DVC and we know how data versioning helps teams. The evolving Generative AI workflows are different and require an evolution of versioning workflows to accomplish Generative AI goals. This new era thrives on vast amounts of unstructured data, which include everything from images, videos, and audio, to MRI scans, document scans, and plain text dialogues. This data, often scaling into billions of objects, together with the resource-consuming task of scoring models on expensive GPU hardware or using model APIs like ChatGPT, brings forth unique challenges in the field of data management and versioning. In this talk, we will delve into data versioning in the context of generative AI. Our focus will be on strategies that assist businesses in minimizing their processing time and the volume of API calls to external models like ChatGPT, resulting in substantial cost savings. Furthermore, we will discuss effective methodologies for sharing datasets amongst ML researchers to promote seamless collaboration. Lastly, we will examine the pivotal transformations generative AI has introduced to data versioning in the past year including annotations and embeddings versioning. Together, these insights will provide attendees with an in-depth understanding of the rapidly evolving data management landscape in the era of generative AI. What You’ll Learn 1. How data management is different in the Generative AI environment compared to traditional ML 2. How to save cost on compute and API calls using data versioning 3. Dataset sharing in the team as a way to improve collaboration 4. How to efficiently version annotation, embeddings, and auto-labels together with data To learn more about our approach see the recent research paper that we presented as a workshop at ICCV in Paris: https://arxiv.org/abs/2309.11608 DVC delivers the best practices of software engineering to your machine learning workflows; setting you up for success! Learn more about our ecosystem of tools at https://dvc.ai *Try out the DVC Extension for VS Code here:* https://marketplace.visualstudio.com/items?itemName=Iterative.dvc To learn more about Iterative's open-source and SaaS tools please visit: 🧑🏽💻 *Our free online course:* https://learn.iterative.ai ✍🏼 *Our docs:* https://dvc.org/doc (Data Version Control, Pipelines, Experiments) https://cml.dev/doc (CI/CD for Machine Learning) https://studio.iterative.ai (Team Collaboration, Experiments, Model Registry) *Join the Community on our Discord server:* https://discord.gg/W49xzNmycw #dvc #machinelearning #datascience #generativeai
DVC Extension for VS Code Update: Plots Wizard
In this video demo, Julie Galvan showcases the latest update to the DVC VS Code extension: a new Plots Wizard. Now, you can easily add plots to your dvc.yaml file. Julie guides you through the process, from selecting data files, and the plot template, to picking metrics for axes, which produces the code in your dvc.yml file and ultimately your plot. You can find more info in this release in the DVC for VS Code v. 1.0.54. Release notes: https://github.com/iterative/vscode-dvc/releases/tag/1.0.54 DVC delivers the best practices of software engineering to your machine learning workflows; setting you up for success! Learn more about our ecosystem of tools at https://dvc.ai *Try out the DVC Extension for VS Code here:* https://marketplace.visualstudio.com/items?itemName=Iterative.dvc To learn more about Iterative's open-source and SaaS tools please visit: 🧑🏽💻 *Our free online course:* https://learn.iterative.ai ✍🏼 *Our docs:* https://dvc.org/doc (Data Version Control, Pipelines, Experiments) https://cml.dev/doc (CI/CD for Machine Learning) https://studio.iterative.ai (Team Collaboration, Experiments, Model Registry) *Join the Community on our Discord server:* https://discord.gg/W49xzNmycw #dvc #machinelearning #datascience #generativeai
DataChain Open-Source Release - A new way to manage your Unstructured Data
DataChain Open-Source Release - A new way to manage your Unstructured Data ⭐️ Star the repo and get started: https://github.com/iterative/datachain See Dmitry's blog post on the thought process behind the tool: https://dvc.ai/blog/datachain-release Find out more at https://dvc.ai
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