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Haeryong Rhim

Member since 2022

Silver League

3700 points
Google DeepMind: 02 Represent Your Language Data Earned May 31, 2026 EDT
生成式 AI 適用的機器學習運作 (MLOps) Earned May 31, 2026 EDT
AI Boost Bites:個人意見回饋代理 Earned May 31, 2026 EDT
Google DeepMind: 01 Build Your Own Small Language Model Earned May 31, 2026 EDT
Google DeepMind:訓練小型語言模型 Earned May 31, 2026 EDT
生成式 AI 簡介 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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本課程旨在提供必要的知識和工具,協助您探索機器學習運作團隊在部署及管理生成式 AI 模型時面臨的獨特挑戰,並瞭解 Vertex AI 如何幫 AI 團隊簡化機器學習運作程序,打造成效非凡的生成式 AI 專案。

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這部影片說明如何使用 Gemini Gem 建構個人化的「工作夥伴」代理,簡化基本意見回饋,讓會議更具策略性且更有效率。

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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「Google DeepMind:訓練小型語言模型」技能徽章進階課程,即可證明您具備下列技能: 提出實際的語言模型研究問題、建構簡單的分詞器、準備資料集來訓練 Transformer 語言模型,以及執行小型語言模型的訓練迴圈。 註冊免付費訂閱方案,即可免付費使用這個實驗室。每個月還能獲得 35 點免付費抵免額!

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這個入門微學習課程主要說明生成式 AI 的定義和使用方式,以及此 AI 與傳統機器學習方法的差異。本課程也會介紹各項 Google 工具,協助您開發自己的生成式 AI 應用程式。

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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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