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Terapkan keterampilan Anda di Konsol Google Cloud

Ruben Schulze

Menjadi anggota sejak 2023

Getting Started with Apache Beam Earned Feb 8, 2024 EST
Production Machine Learning Systems Earned Des 26, 2023 EST
Machine Learning in the Enterprise Earned Des 11, 2023 EST
Feature Engineering Earned Nov 9, 2023 EST
Build, Train and Deploy ML Models with Keras on Google Cloud Earned Nov 3, 2023 EDT
Launching into Machine Learning Earned Okt 29, 2023 EDT
Pengantar AI dan Machine Learning di Google Cloud Earned Sep 26, 2023 EDT
Google Cloud Big Data and Machine Learning Fundamentals Earned Sep 24, 2023 EDT

Learn how to write and test pipelines with Dataflow and Apache Beam

Pelajari lebih lanjut

This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed training models with custom estimators. This is the second course of the Advanced Machine Learning on Google Cloud series. After completing this course, enroll in the Image Understanding with TensorFlow on Google Cloud course.

Pelajari lebih lanjut

This course takes a real-world approach to the ML Workflow through a case study. An ML team faces several ML business requirements and use cases. The team must understand the tools required for data management and governance and consider the best approach for data preprocessing. The team is presented with three options to build ML models for two use cases. The course explains why they would use AutoML, BigQuery ML, or custom training to achieve their objectives.

Pelajari lebih lanjut

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.

Pelajari lebih lanjut

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

Pelajari lebih lanjut

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.

Pelajari lebih lanjut

Kursus ini memperkenalkan penawaran AI dan machine learning (ML) di Google Cloud yang membangun project AI prediktif dan generatif. Kursus ini akan membahas teknologi, produk, dan alat yang tersedia di seluruh siklus proses data ke AI, yang mencakup fondasi, pengembangan, dan solusi AI. Kursus ini bertujuan membantu data scientist, developer AI, dan engineer ML meningkatkan keterampilan dan pengetahuan mereka melalui pengalaman belajar yang menarik dan latihan praktik langsung.

Pelajari lebih lanjut

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.

Pelajari lebih lanjut