Category: Intermediate (200)

February 2024: This post was reviewed and updated for accuracy. This post is co-written with Thatcher Thornberry from bpx energy.  Facies classification is the process of segmenting lithologic formations from geologic data at the wellbore location. During drilling, wireline logs are obtained, which have depth-dependent geologic information. Geologists are deployed to analyze this log data […]

Amazon Textract is a machine learning (ML) service that automatically extracts text, handwriting, and data from any document or image. To make it simpler to evaluate the capabilities of Amazon Textract, we have launched a new Bulk Document Uploader feature on the Amazon Textract console that enables you to quickly process your own set of […]

Amazon SageMaker comes with two options to spin up fully managed notebooks for exploring data and building machine learning (ML) models. The first option is fast start, collaborative notebooks accessible within Amazon SageMaker Studio—a fully integrated development environment (IDE) for machine learning. You can quickly launch notebooks in Studio, easily dial up or down the […]

You can now register machine learning (ML) models built in Amazon SageMaker Canvas with a single click to the Amazon SageMaker Model Registry, enabling you to operationalize ML models in production. Canvas is a visual interface that enables business analysts to generate accurate ML predictions on their own—without requiring any ML experience or having to […]

Jupyter notebooks are highly favored by data scientists for their ability to interactively process data, build ML models, and test these models by making inferences on data. However, there are scenarios in which data scientists may prefer to transition from interactive development on notebooks to batch jobs. Examples of such use cases include scaling up […]

Time series forecasting refers to the process of predicting future values of time series data (data that is collected at regular intervals over time). Simple methods for time series forecasting use historical values of the same variable whose future values need to be predicted, whereas more complex, machine learning (ML)-based methods use additional information, such […]

Support for AWS DeepComposer will be ending soon. Please see Support for AWS DeepComposer ending soon for more details. Generative AI is gaining a lot of public attention at present, with talk around products such as GPT4, ChatGPT, DALL-E2, Bard, and many other AI technologies. Many customers have been asking for more information on AWS’s […]

This post is co-written by Jyoti Sharma and Sharmo Sarkar from Vericast. For any machine learning (ML) problem, the data scientist begins by working with data. This includes gathering, exploring, and understanding the business and technical aspects of the data, along with evaluation of any manipulations that may be needed for the model building process. […]

Machine learning (ML) helps organizations generate revenue, reduce costs, mitigate risk, drive efficiencies, and improve quality by optimizing core business functions across multiple business units such as marketing, manufacturing, operations, sales, finance, and customer service. With AWS ML, organizations can accelerate the value creation from months to days. Amazon SageMaker Canvas is a visual, point-and-click […]

Today, we announce the availability of sample notebooks that demonstrate question answering tasks using a Retrieval Augmented Generation (RAG)-based approach with large language models (LLMs) in Amazon SageMaker JumpStart. Text generation using RAG with LLMs enables you to generate domain-specific text outputs by supplying specific external data as part of the context fed to LLMs. […]