У нас вы можете посмотреть бесплатно Learn Live - Azure ML Fundamentals или скачать в максимальном доступном качестве, видео которое было загружено на ютуб. Для загрузки выберите вариант из формы ниже:
Если кнопки скачивания не
загрузились
НАЖМИТЕ ЗДЕСЬ или обновите страницу
Если возникают проблемы со скачиванием видео, пожалуйста напишите в поддержку по адресу внизу
страницы.
Спасибо за использование сервиса ClipSaver.ru
Full series information: https://aka.ms/learnlive-202302FT More info here: https://aka.ms/learnlive-202302FT-Ep9 Follow on Microsoft Learn: Session documentation: https://aka.ms/learnlive-20230404FT In the Azure ML Fundamentals session, you will get an understanding of the overall Azure Machine Learning (AzureML) components and how you can start using the AzureML studio web portal to accelerate you AI journey in the cloud. --------------------- Learning objectives Intro to Azure ML Service Implement ML solution in Azure ML Service and Azure ML Studio leveraging, Azure ML assets, notebooks, AutoML and SDK V2 --------------------- Chapters -------- 00:00 - Welcome 00:55 - Introduction 02:02 - Learning Objectives 13:58 - Where do we start? - Azure Machine Learning Service and Access Control 23:05 - Azure Machine Learning Studio - Let us create our Compute for Data Science activities 27:04 - Authoring Experience for your Notebook - Use Azure ML Python SDK to manage our ML Model Life Cycle 34:27 - Create Data Assets from your choice of Data Store to train your ML Model. 54:47 - Model Authoring - Generate your model through Automated ML with high scale, efficiency, and productivity all while sustaining model quality - Demo 56:47 - Register your model to Azure ML Models registry 1:05:55 - Deploy your Model to a Managed Endpoint, I Realtime Endpoint Demo 1:10:05 - Inferencing - Scoring against your model Endpoint 1:17:18 - Designer can help you put together a model pipeline very easily - creates the code for scoring script and creates the environment yml file for your model 1:19:15 - Q & A - When you do not have a target variable for your model, un-supervised learning algorithm (regression) might the option you select during Automated ML 1:21:23 - Closure --------------------- Presenters Meer Alam Azure Customer Engineer Microsoft LinkedIn: / meeralam Marco Aurelio Cardoso Azure Customer Engineer Microsoft LinkedIn: / marco-cardoso Moderators Neeraj Jhaveri Senior FastTrack Engineer Microsoft LinkedIn: / neerajjhaveri