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Robert Alexandru Dobre

成为会员时间：2023

白银联赛

5685 积分
Introduction to AI and Machine Learning on Google Cloud - 繁體中文徽章 Introduction to AI and Machine Learning on Google Cloud - 繁體中文 Earned Sep 22, 2023 EDT
Build, Train and Deploy ML Models with Keras on Google Cloud徽章 Build, Train and Deploy ML Models with Keras on Google Cloud Earned Sep 21, 2023 EDT
Launching into Machine Learning徽章 Launching into Machine Learning Earned Sep 12, 2023 EDT
How Google Does Machine Learning徽章 How Google Does Machine Learning Earned Sep 8, 2023 EDT
Google Cloud Big Data and Machine Learning Fundamentals徽章 Google Cloud Big Data and Machine Learning Fundamentals Earned Aug 28, 2023 EDT
Generative AI Fundamentals - 繁體中文徽章 Generative AI Fundamentals - 繁體中文 Earned Aug 25, 2023 EDT
Introduction to Responsible AI - 繁體中文徽章 Introduction to Responsible AI - 繁體中文 Earned Aug 25, 2023 EDT
Introduction to Large Language Models - 繁體中文徽章 Introduction to Large Language Models - 繁體中文 Earned Aug 25, 2023 EDT
Introduction to Generative AI - 繁體中文徽章 Introduction to Generative AI - 繁體中文 Earned Aug 23, 2023 EDT

本課程介紹 Google Cloud 中的 AI 和機器學習 (ML) 服務。這些服務可建構預測式和生成式 AI 專案。我們將帶您探索「從資料到 AI」生命週期中適用的技術、產品和工具，包括 AI 基礎、開發選項及解決方案。課程目的是藉由生動的學習體驗與實作練習，增進數據資料學家、AI 開發人員和機器學習工程師的技能與知識。

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This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use.

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The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis. We describe Vertex AI AutoML and how to build, train, and deploy an ML model without writing a single line of code. You will understand the benefits of Big Query ML. We then discuss how to optimize a machine learning (ML) model and how generalization and sampling can help assess the quality of ML models for custom training.

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This course explores what ML is and what problems it can solve. The course also discusses best practices for implementing machine learning. You’re introduced to Vertex AI, a unified platform to quickly build, train, and deploy AutoML machine learning models. The course discusses the five phases of converting a candidate use case to be driven by machine learning, and why it’s important to not skip them. The course ends with recognizing the biases that ML can amplify and how to recognize them.

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This course introduces the Google Cloud big data and machine learning products and services that support the data-to-AI lifecycle. It explores the processes, challenges, and benefits of building a big data pipeline and machine learning models with Vertex AI on Google Cloud.

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完成「Introduction to Generative AI」、「Introduction to Large Language Models」和「Introduction to Responsible AI」課程，即可獲得技能徽章。通過最終測驗，就能展現您對生成式 AI 基本概念的掌握程度。 「技能徽章」是 Google Cloud 核發的數位徽章，用於表彰您對 Google Cloud 產品和服務的相關知識。您可以將技能徽章公布在社群媒體的個人資料中，向其他人分享您的成果。

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這個入門微學習課程主要介紹「負責任的 AI 技術」和其重要性，以及 Google 如何在自家產品中導入這項技術。本課程也會說明 Google 的 7 個 AI 開發原則。

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這是一堂入門級的微學習課程，旨在探討大型語言模型 (LLM) 的定義和用途，並說明如何調整提示來提高 LLM 成效。此外，也會介紹多項 Google 工具，協助您自行開發生成式 AI 應用程式。

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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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