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.
-1-Designing-and-Implementing-Data-Storage-main-resized.jpg)
کورس یادگیری Microsoft Azure Data Engineering (DP-203) : طراحی و پیاده سازی Data Storage

AWS Solutions Architect Professional (SAP-C02) Cert Prep: 2 Design for New Solutions

Google Cloud Professional Machine Learning Engineer Cert Prep: 1 Framing ML Problems

Google Cloud Professional Machine Learning Engineer Cert Prep: 6 Monitoring, Optimizing, and Maintaining ML Solutions

Google Cloud Professional Machine Learning Engineer Cert Prep: 4 Developing ML Models

دوره تست برنامه های پایتون بوسیله Pytest

Google Cloud Professional Data Engineer Cert Prep: 1 Designing Data Processing Systems

شش عنصر کلیدی MLOps

مقایسه Github Actions با AWS Code Build

AWS Certified Data Analytics – Specialty (DAS-C01) Cert Prep: 4 Analysis and Visualization
✨ تا ۷۰% تخفیف با شارژ کیف پول 🎁
مشاهده پلن ها