包阅导读总结
1. 关键词：AWS、Amazon Q Developer、SageMaker Studio、ML Workflows、Generative AI
2. 总结：AWS 在 Amazon SageMaker Studio 中引入 Amazon Q Developer，这是一款原生的生成式 AI 助手，能简化和加速 ML 开发流程，提供工具推荐、代码生成等帮助，已在所有可用区域推出，适用于特定用户，且有定价信息。
3. 主要内容：
– AWS 新动作：宣布 Amazon SageMaker Studio 新增 Amazon Q Developer 功能
– 功能特点：
– 内置于 SageMaker 的 JupyterLab 体验
– 为各任务推荐最佳工具、提供分步指导、生成代码和故障排除协助
– 助用户简化 ML 开发周期，无需离开 Studio 搜索资源
– 能力展示：
– 生成各种 ML 任务的代码
– 提供调试和错误修复的指导
– 给出日程安排建议
– 相关情况：
– 可在 JupyterLab 中启动模型开发周期，提供聊天能力
– 类似工具还有 RapidMiner 等
– 在所有 SageMaker 可用区域推出，特定用户可用，定价见页面
思维导图：
文章来源：infoq.com
作者：Daniel Dominguez
发布时间：2024/7/24 0:00
语言：英文
总字数：367字
预计阅读时间：2分钟
评分：86分
标签：AWS,Amazon SageMaker,Amazon Q 开发者,机器学习,AI 助手
以下为原文内容
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AWS announced that Amazon SageMaker Studio now includes Amazon Q Developer as a new capability. This generative AI-powered assistant is built natively into SageMaker’s JupyterLab experience and provides recommendations for the best tools for each task, step-by-step guidance, code generation, and troubleshooting assistance.
Amazon Q Developer is designed to simplify and accelerate the ML development lifecycle by allowing users to build, train, and deploy ML models without leaving SageMaker Studio to search for sample notebooks, code snippets, and instructions. It can help with translating complex ML problems into smaller tasks and searching for relevant information in documentation.
The assistant is capable of generating code for various ML tasks, such as training an XGBoost algorithm for prediction or downloading a dataset from S3 and reading it using Pandas. It can also provide guidance for debugging and fixing errors, as well as recommendations for scheduling a notebook job.
JupyterLab in SageMaker Studio can now kick off the modeldevelopment lifecycle with Amazon Q Developer. It provides chat capability to discover and learn how to leverage SageMaker features for use cases without having to sift through extensive documentation. The assistant can also generate code tailored to the user’s needs and provide in-line code suggestions and conversational assistance to edit, explain, and document code in JupyterLab.
Ricardo Ferreira, DevRel for AWS, shares on his X account:
Silly coding mistakes are okay when you’re learning a programming language. But not so much as you progress in your software development career. #AmazonQDeveloper can help you with this.
AWS Developer Advocate Romain Jourdan, posted on X:
The generative AI space is moving so fast that it is difficult to catch up. Amazon Q Developer is improving every week too so we wanted to make it easy for developers to know what’s new, and what to test.
Other similar tools include RapidMiner, H2O.ai, KNIME, and Alteryx. These tools offer automated machine learning, data preparation, and model deployment capabilities and can help streamline the development process and increase productivity.
Amazon Q Developer is now available in all regions where Amazon SageMaker is generally available. It is available for all Amazon Q Developer Pro Tier users, with pricing information available on the Amazon Q Developer pricing page.
