Учасник із 2023
Automate Data Capture at Scale with Document AI
Earned бер. 18, 2024 EDT
Feature Engineering
Earned груд. 27, 2023 EST
Build, Train and Deploy ML Models with Keras on Google Cloud
Earned груд. 18, 2023 EST
Launching into Machine Learning
Earned лист. 17, 2023 EST
Introduction to AI and Machine Learning on Google Cloud
Earned лист. 1, 2023 EDT
Earn the introductory skill badge by completing the Automate Data Capture at Scale with Document AI course. In this course, you learn how to extract, process, and capture data using Document AI.
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.
This course covers building ML models with TensorFlow and Keras, improving the accuracy of ML models and writing ML models for scaled use.
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.
This course introduces Google Cloud's AI and machine learning (ML) capabilities, with a focus on developing both generative and predictive AI projects. It explores the various technologies, products, and tools available throughout the data-to-AI lifecycle, empowering data scientists, AI developers, and ML engineers to enhance their expertise through interactive exercises.