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Haeryong Rhim

成为会员时间:2022

白银联赛

3700 积分
Google DeepMind: 02 Represent Your Language Data Earned May 31, 2026 EDT
适用于生成式 AI 的机器学习运维 (MLOps) Earned May 31, 2026 EDT
AI Boost Bites:您的个人反馈智能体 Earned May 31, 2026 EDT
Google DeepMind: 01 Build Your Own Small Language Model Earned May 31, 2026 EDT
Google DeepMind:训练小语言模型 Earned May 31, 2026 EDT
生成式 AI 简介 Earned Sep 20, 2023 EDT
Cloud Hero: Kubernetes Earned Nov 22, 2022 EST
Deprecated Kubernetes Solutions Earned Oct 31, 2022 EDT

In this Google DeepMind course you will learn how to prepare text data for language models to process. You will investigate the tools and techniques used to prepare, structure, and represent text data for language models, with a focus on tokenization and embeddings. You will be encouraged to think critically about the decisions behind data preparation, and what biases within the data may be introduced into models. You will analyze trade-offs, learn how to work with vectors and matrices, how meaning is represented in language models. Finally, you will practice designing a dataset ethically using the Data Cards process, ensuring transparency, accountability, and respect for community values in AI development.

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本课程致力于为您提供所需的知识和工具,让您能够了解 MLOps 团队在部署和管理生成式 AI 模型以及探索 Vertex AI 如何帮助 AI 团队简化 MLOps 流程时面临的独特挑战,并帮助您在生成式 AI 项目中取得成功。

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本视频介绍了如何使用 Gemini Gem 构建个性化的“Work with Me”智能体,帮助您简化基础反馈,让会议更具战略性和效率。

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In this Google DeepMind course, you will learn the fundamentals of language models and gain a high-level understanding of the machine learning development pipeline. You will consider the strengths and limitations of traditional n-gram models and advanced transformer models. Practical coding labs will enable you to develop insights into how machine learning models work and how they can be used to generate text and identify patterns in language. Through real-world case studies, you will build an understanding around how research engineers operate. Drawing on these insights you will identify problems that you wish to tackle in your own community and consider how to leverage the power of machine learning responsibly to address these problems within a global and local context.

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完成本课程,赢取 Google DeepMind:训练小语言模型高级技能徽章,展示您在以下方面的技能: 提出实际的语言模型研究问题;构建一个简单的词元化器;制作用于训练 Transformer 语言模型的数据集;运行小语言模型的训练循环。 注册免费订阅,即可免费访问此实验。每月可免费获得 35 个点数!

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这是一节入门级微课程,旨在解释什么是生成式 AI、它的用途以及与传统机器学习方法的区别。该课程还介绍了可以帮助您开发自己的生成式 AI 应用的各种 Google 工具。

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Get ready for a challenge - learn how Kubernetes Engine brings the latest innovations in developer productivity, resource efficiency, automated operations, and open source flexibility to accelerate your time to market. Learn how to take advantage of Google Cloud's powerful tools and challenge yourself to complete each lab as quickly and accurately as possible to score points and earn badges!

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Containerized applications have changed the game and are here to stay. With Kubernetes, you can orchestrate containers with ease, and integration with the Google Cloud Platform is seamless. In this advanced-level quest, you will be exposed to a wide range of Kubernetes use cases and will get hands-on practice architecting solutions over the course of 8 labs. From building Slackbots with NodeJS, to deploying game servers on clusters, to running the Cloud Vision API, Kubernetes Solutions will show you first-hand how agile and powerful this container orchestration system is.

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