加入 登录

Valeriia Boldyrieva

成为会员时间：2022

黄金联赛

8995 积分
Deploy an Agent with Agent Development Kit (ADK) Earned Nov 27, 2025 EST
使用智能体开发套件 (ADK) 和 Agent Engine 部署多智能体系统 Earned Nov 27, 2025 EST
Natural Language Processing on Google Cloud Earned Jan 11, 2024 EST
Feature Engineering Earned Jan 3, 2024 EST
Build, Train and Deploy ML Models with Keras on Google Cloud Earned Nov 25, 2022 EST
Launching into Machine Learning Earned Nov 15, 2022 EST
How Google Does Machine Learning Earned Nov 1, 2022 EDT
Google Cloud Big Data and Machine Learning Fundamentals Earned Oct 18, 2022 EDT

In this challenge lab, you will demonstrate your ability to author agents using Agent Development Kit (ADK), deploy those agents to Agent Engine, and use them from a web app. Complete the challenge lab to earn a Google Cloud skill badge.

了解详情

在本课程中，您将学习如何使用 Google 智能体开发套件构建复杂的多智能体系统。您将构建搭载工具的智能体，利用父子层级关系和工作流进行连接，以此定义它们的交互方式。您将在本地运行智能体，将其部署到 Vertex AI Agent Engine 并作为托管式智能体流运行，基础设施决策和资源扩缩则由 Agent Engine 处理。请注意，这些实验基于此产品的预发布版本。在进行维护更新时，这些实验可能会出现一些延迟。

了解详情

This course introduces the products and solutions to solve NLP problems on Google Cloud. Additionally, it explores the processes, techniques, and tools to develop an NLP project with neural networks by using Vertex AI and TensorFlow.

了解详情

This course explores the benefits of using Vertex AI Feature Store, how to improve the accuracy of ML models, and how to find which data columns make the most useful features. This course also includes content and labs on feature engineering using BigQuery ML, Keras, and TensorFlow.

了解详情

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

了解详情

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.

了解详情

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.

了解详情

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.

了解详情