AWS Machine Learning Blog

AUGUST 8, 2024

This post highlights how Twilio enabled natural language-driven data exploration of business intelligence (BI) data with RAG and Amazon Bedrock. Twilio’s use case Twilio wanted to provide an AI assistant to help their data analysts find data in their data lake.

Metadata 117

Metadata LLM Prompt Engineer Prompt Engineering 117

AWS Machine Learning Blog

APRIL 5, 2023

Data overview and preparation You can use a SageMaker Studio notebook with a Python 3 (Data Science) kernel to run the sample code. The dataset is a collection of 147,702 product listings with multilingual metadata and 398,212 unique catalogue images. We use the first metadata file in this demo.

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Metadata Neural Network ML Python 105

AWS Machine Learning Blog

MAY 4, 2023

Each dataset group can have up to three datasets, one of each dataset type: target time series (TTS), related time series (RTS), and item metadata. A dataset is a collection of files that contain data that is relevant for a forecasting task. DatasetGroupFrequencyTTS The frequency of data collection for the TTS dataset.

Automation 118

Automation Metadata Data Ingestion Data Scientist 118

AWS Machine Learning Blog

OCTOBER 2, 2024

Additionally, you can enable model invocation logging to collect invocation logs, full request response data, and metadata for all Amazon Bedrock model API invocations in your AWS account. Tanvi Singhal is a Data Scientist within AWS Professional Services.

Generative AI 117

Generative AI Data Ingestion AI AI 117

ODSC - Open Data Science

JULY 26, 2024

Streamlining Unstructured Data for Retrieval Augmented Generatio n Matt Robinson | Open Source Tech Lead | Unstructured Learn about the complexities of handling unstructured data, and practical strategies for extracting usable text and metadata from it. You’ll also discuss loading processed data into destination storage.

Data Scientist 52

Data Scientist Robotics Data Science Metadata 52

AWS Machine Learning Blog

JANUARY 6, 2023

In this post, we illustrate how to handle OOC by utilizing the power of the IMDb dataset (the premier source of global entertainment metadata) and knowledge graphs. Creates a Lambda function to process and load movie metadata and embeddings to OpenSearch Service indexes ( **-ReadFromOpenSearchLambda-** ).

Metadata 97

Metadata Machine Learning ML Data Scientist 97

ODSC - Open Data Science

SEPTEMBER 17, 2024

Streamlining Unstructured Data for Retrieval Augmented Generation Matt Robinson | Open Source Tech Lead | Unstructured In this talk, you’ll explore the complexities of handling unstructured data, and offer practical strategies for extracting usable text and metadata from unstructured data.

LLM 52

LLM Large Language Models Metadata Data Science 52

deepsense.ai

JULY 30, 2023

Preceded by data analysis and feature engineering, a model is trained and ready to be productionized. We may observe a growing awareness among machine learning and data science practitioners of the crucial role played by pre- and post-training activities. During training, we log all the model metrics and metadata automatically.

Large Language Models 98

Large Language Models LLM Machine Learning Automation 98

ODSC - Open Data Science

FEBRUARY 25, 2025

Data Engineering TrackBuild the Data Foundation forAI Data engineering powers every AI system. This track offers practical guidance on building scalable data pipelines and ensuring dataquality.

Data Scientist 52

Data Scientist Machine Learning Large Language Models ML Engineer 52

Mlearning.ai

FEBRUARY 16, 2023

Arranging Efficient Data Streams Modern companies typically receive data from multiple sources. Therefore, quick data ingestion for instant use can be challenging. Furthermore, a shared-data approach stems from this efficient combination. Superior data protection.

Business Intelligence 52

Business Intelligence Data Ingestion Metadata Machine Learning 52

Pickl AI

OCTOBER 19, 2023

Ensure that everyone handling data understands its importance and the role it plays in maintaining data quality. Data Documentation Comprehensive data documentation is essential. Create data dictionaries and metadata repositories to help users understand the data’s structure and context.

Data Quality 52

Data Quality ETL Machine Learning Data Ingestion 52

Heartbeat

NOVEMBER 6, 2023

You might need to extract the weather and metadata information about the location, after which you will combine both for transformation. In the image, you can see that the extract the weather data and extract metadata information about the location need to run in parallel. This type of execution is shown below.

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ETL Python Metadata Deep Learning 52

The MLOps Blog

MAY 9, 2023

The components comprise implementations of the manual workflow process you engage in for automatable steps, including: Data ingestion (extraction and versioning). Data validation (writing tests to check for data quality). Data preprocessing. Let’s briefly go over each of the components below. CSV, Parquet, etc.)

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ML Machine Learning Metadata Data Science 98

The MLOps Blog

MARCH 21, 2023

To make that possible, your data scientists would need to store enough details about the environment the model was created in and the related metadata so that the model could be recreated with the same or similar outcomes. Your ML platform must have versioning in-built because code and data mostly make up the ML system.

Machine Learning 69

Machine Learning Data Scientist ML Metadata 69