Flipboard

AUGUST 17, 2023

Many practitioners are extending these Redshift datasets at scale for machine learning (ML) using Amazon SageMaker , a fully managed ML service, with requirements to develop features offline in a code way or low-code/no-code way, store featured data from Amazon Redshift, and make this happen at scale in a production environment.

ML 123

ML Auto-complete Auto-classification Machine Learning 123

AWS Machine Learning Blog

NOVEMBER 15, 2024

In the metadata.jsonl file, each example is a dictionary that contains three keys named file_name , prompt , and completion. prompt defines the text input prompt and completion defines the text completion corresponding to the input prompt. jpg", "prompt": "what is the contact person name mentioned in letter?", "completion": "P.

Auto-complete 93

Auto-complete ML Python AI Modeling 93

AWS Machine Learning Blog

NOVEMBER 9, 2023

Building out a machine learning operations (MLOps) platform in the rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML) for organizations is essential for seamlessly bridging the gap between data science experimentation and deployment while meeting the requirements around model performance, security, and compliance.

Data Drift 118

Data Drift Auto-complete ML Automation 118

AWS Machine Learning Blog

MAY 12, 2023

Amazon SageMaker comes with two options to spin up fully managed notebooks for exploring data and building machine learning (ML) models. In addition to creating notebooks, you can perform all the ML development steps to build, train, debug, track, deploy, and monitor your models in a single pane of glass in Studio.

Auto-complete 89

Auto-complete Machine Learning Python ML 89

ODSC - Open Data Science

FEBRUARY 28, 2023

Going from Data to Insights LexisNexis At HPCC Systems® from LexisNexis® Risk Solutions you’ll find “a consistent data-centric programming language, two processing platforms, and a single, complete end-to-end architecture for efficient processing.” These tools are designed to help companies derive insights from big data.

Data Science 96

Data Science Auto-complete Machine Learning AI 96

AWS Machine Learning Blog

JUNE 15, 2023

When the job is complete, the parallel data status shows as Active and is ready to use. When the job status changes into Completed , we can find the translated documents in Chinese (D2L-zh) in the S3 bucket output folder. We can check the training job progress on the Amazon Translate console.

Auto-complete 85

Auto-complete Natural Language Processing Deep Learning Machine Learning 85

AWS Machine Learning Blog

DECEMBER 14, 2023

Amazon SageMaker Studio offers a broad set of fully managed integrated development environments (IDEs) for machine learning (ML) development, including JupyterLab, Code Editor based on Code-OSS (Visual Studio Code Open Source), and RStudio. It’s attached to a ML compute instance whenever a Space is run. Choose Create JupyterLab space.

Generative AI 117

Generative AI AI Tools ML Auto-complete 117