An introduction to MLOps with TensorFlow Extended (TFX)

Автор: TensorFlow

Загружено: 2022-05-12

Просмотров: 11554

Описание:

Deploying advanced machine learning technology to serve customers and/or business needs requires a rigorous approach and production-ready systems. An ML application in production requires modern software development methodology, as well as issues unique to ML and data science. Hear about the importance of MLOps, the use of ML pipeline architectures for implementing production ML applications, rigorous analysis of model performance and sensitivity, and review Google’s experience with TensorFlow Extended (TFX).

Resources:
TensorFlow website → https://goo.gle/3KejoUZ
TFX-Addons → https://goo.gle/3x6IOju
Become a Machine Learning expert → https://goo.gle/mlops-courses

Speaker: Robert Crowe

Watch more:
All Google I/O 2022 Sessions → https://goo.gle/IO22_AllSessions
ML/AI at I/O 2022 playlist → https://goo.gle/IO22_ML-AI
All Google I/O 2022 technical sessions → https://goo.gle/IO22_Sessions

Subscribe to TensorFlow → https://goo.gle/TensorFlow

#GoogleIO

An introduction to MLOps with TensorFlow Extended (TFX)

Доступные форматы для скачивания:

Скачать видео mp4

Информация по загрузке:

Скачать аудио mp3

Похожие видео

Manage MLOps and deploy Machine Learning to production with the new and improved TFX

Manage MLOps and deploy Machine Learning to production with the new and improved TFX

TFX: Production ML pipelines with TensorFlow (TF World '19)

TFX: Production ML pipelines with TensorFlow (TF World '19)

Machine Learning Zero to Hero (Google I/O'19)

Machine Learning Zero to Hero (Google I/O'19)

Kubernetes — Простым Языком на Понятном Примере

Kubernetes — Простым Языком на Понятном Примере

Does your app use ML? Make it a product with TFX | Session

Does your app use ML? Make it a product with TFX | Session

RAG простыми словами: как научить LLM работать с файлами

RAG простыми словами: как научить LLM работать с файлами

How to structure your ML project code

How to structure your ML project code

Что такое стек ИИ? Магистратура LLM, RAG и аппаратное обеспечение ИИ

Что такое стек ИИ? Магистратура LLM, RAG и аппаратное обеспечение ИИ

Introduction to MLOps and Vertex Pipelines

Introduction to MLOps and Vertex Pipelines

Объяснение MLOps | Основы машинного обучения

Объяснение MLOps | Основы машинного обучения

Intro to JAX: Accelerating Machine Learning research

Intro to JAX: Accelerating Machine Learning research

КАК УСТРОЕН TCP/IP?

КАК УСТРОЕН TCP/IP?

⚡️Спецслужбы Запада зашли в Москву || Армия РФ отошла?

⚡️Спецслужбы Запада зашли в Москву || Армия РФ отошла?

From Experimentation to Products: The Production Machine Learning Journey • Robert Crowe • GOTO 2021

From Experimentation to Products: The Production Machine Learning Journey • Robert Crowe • GOTO 2021

Serving Machine Learning models with Google Vertex AI

Serving Machine Learning models with Google Vertex AI

PyTorch on Vertex AI

PyTorch on Vertex AI

MLFlow: A Quickstart Guide

MLFlow: A Quickstart Guide

Apache Iceberg: что это такое и почему все о нем говорят.

Apache Iceberg: что это такое и почему все о нем говорят.

Taking Machine Learning from Research to Production • Robert Crowe • GOTO 2019

Taking Machine Learning from Research to Production • Robert Crowe • GOTO 2019

Transfer learning and Transformer models (ML Tech Talks)

Transfer learning and Transformer models (ML Tech Talks)