成为会员时间：2024
Natural Language Processing on Google Cloud
Earned Oct 13, 2024 EDT
Launching into Machine Learning
Earned Jun 22, 2024 EDT
Google Cloud 的 AI 和機器學習服務簡介
Earned Jun 15, 2024 EDT
Computer Vision Fundamentals with Google Cloud
Earned May 24, 2024 EDT
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.
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.
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。
This course describes different types of computer vision use cases and then highlights different machine learning strategies for solving these use cases. The strategies vary from experimenting with pre-built ML models through pre-built ML APIs and AutoML Vision to building custom image classifiers using linear models, deep neural network (DNN) models or convolutional neural network (CNN) models. The course shows how to improve a model's accuracy with augmentation, feature extraction, and fine-tuning hyperparameters while trying to avoid overfitting the data. The course also looks at practical issues that arise, for example, when one doesn't have enough data and how to incorporate the latest research findings into different models. Learners will get hands-on practice building and optimizing their own image classification models on a variety of public datasets in the labs they will work on.