در حال حاضر محصولی در سبد خرید شما وجود ندارد.
Earning the Google Professional Machine Learning Engineer certification demonstrates your ability to design, build, and productionize machine learning models to solve business challenges using Google Cloud technologies, and knowledge of proven ML models and techniques.
In this fifth course in the certification prep series, instructor Noah Gift covers core concepts relating to automating and orchestrating ML pipelines. Noah explains how to design and implement training pipelines, including how to engineer prompts for Google BigQuery with ChatGPT4. Then, learn about implementing serving pipelines, as Noah explains some of the characteristics of GPU-enabled Docker containers, gives a Rust PyTorch microservice walkthrough, and demos a Rust pre-trained PyTorch microservice.
در این روش نیاز به افزودن محصول به سبد خرید و تکمیل اطلاعات نیست و شما پس از وارد کردن ایمیل خود و طی کردن مراحل پرداخت لینک های دریافت محصولات را در ایمیل خود دریافت خواهید کرد.
Azure Data Engineer Associate (DP-203) Cert Prep: 3 Design and Implement Data Security
Google Cloud Professional Machine Learning Engineer Cert Prep: 1 Framing ML Problems
Databricks Certified Data Engineer Associate Cert Prep: 2 ELT with Spark SQL and Python
کار با توابع Google Cloud
کار بر روی داده ها بوسیله زبان Python
Google Cloud Professional Data Engineer Cert Prep: 1 Designing Data Processing Systems
یادگیری کامل عملگرها در زبان Swift
شش عنصر کلیدی MLOps
Google Cloud Professional Machine Learning Engineer Cert Prep: 3 Designing Data Preparation and Processing Systems
Google Cloud Professional Data Engineer Cert Prep: 4 Ensuring Solution Quality