AWS Machine Learning Blog

FEBRUARY 27, 2024

The model will be approved by designated data scientists to deploy the model for use in production. For production environments, data ingestion and trigger mechanisms are managed via a primary Airflow orchestration. Pavel Maslov is a Senior DevOps and ML engineer in the Analytic Platforms team.

Machine Learning 119

Machine Learning DevOps Data Quality Data Scientist 119

IBM Journey to AI blog

SEPTEMBER 20, 2023

These include data ingestion, data selection, data pre-processing, FM pre-training, model tuning to one or more downstream tasks, inference serving, and data and AI model governance and lifecycle management—all of which can be described as FMOps.

Large Language Models 228

Large Language Models DevOps AI Modeling Automation 228

AWS Machine Learning Blog

MAY 7, 2024

The service allows for simple audio data ingestion, easy-to-read transcript creation, and accuracy improvement through custom vocabularies. Mateusz Zaremba is a DevOps Architect at AWS Professional Services. Amazon Transcribe’s new ASR foundation model supports 100+ language variants.

Automation 73

Automation Auto-complete DevOps UX Design 73

AWS Machine Learning Blog

JUNE 27, 2023

This blog post is co-written with Marat Adayev and Dmitrii Evstiukhin from Provectus. That is where Provectus , an AWS Premier Consulting Partner with competencies in Machine Learning, Data & Analytics, and DevOps, stepped in.

DevOps 100

DevOps ML Machine Learning Automation 100

AWS Machine Learning Blog

MARCH 1, 2023

MLOps focuses on the intersection of data science and data engineering in combination with existing DevOps practices to streamline model delivery across the ML development lifecycle. An Amazon Comprehend flywheel automates this ML process, from data ingestion to deploying the model in production.

Data Ingestion 88

Data Ingestion DevOps Automation ML 88

TensorFlow

JANUARY 18, 2023

In this blog post, we discuss the crucial details of building an end-to-end ML pipeline for Semantic Segmentation tasks with TFX and various Google Cloud services such as Dataflow, Vertex Pipelines, Vertex Training, and Vertex Endpoint. TFX Pipeline The ML pipeline is written entirely in TFX, from data ingestion to model deployment.

Data Ingestion 52

Data Ingestion ML DevOps Automation 52

AWS Machine Learning Blog

APRIL 26, 2023

Data engineering – Identifies the data sources, sets up data ingestion and pipelines, and prepares data using Data Wrangler. Data science – The heart of ML EBA and focuses on feature engineering, model training, hyperparameter tuning, and model validation.

ML 94

ML Machine Learning Data Science Data Drift 94