Artificial Intelligence

Category: Amazon SageMaker

Automate a shared bikes and scooters classification model with Amazon SageMaker Autopilot

February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. Amazon SageMaker Autopilot makes it possible for organizations to quickly build and deploy an end-to-end machine learning (ML) model and inference pipeline with just a few lines of code or even without […]

Improve high-value research with Hugging Face and Amazon SageMaker asynchronous inference endpoints

Many of our AWS customers provide research, analytics, and business intelligence as a service. This type of research and business intelligence enables their end customers to stay ahead of markets and competitors, identify growth opportunities, and address issues proactively. For example, some of our financial services sector customers do research for equities, hedge funds, and […]

Balance your data for machine learning with Amazon SageMaker Data Wrangler

August 2023: This post was reviewed for accuracy. Amazon SageMaker Data Wrangler is a new capability of Amazon SageMaker that makes it faster for data scientists and engineers to prepare data for machine learning (ML) applications by using a visual interface. It contains over 300 built-in data transformations so you can quickly normalize, transform, and […]

Launch processing jobs with a few clicks using Amazon SageMaker Data Wrangler

August 2023: This post was reviewed for accuracy. Amazon SageMaker Data Wrangler makes it faster for data scientists and engineers to prepare data for machine learning (ML) applications by using a visual interface. Previously, when you created a Data Wrangler data flow, you could choose different export options to easily integrate that data flow into […]

Prepare and analyze JSON and ORC data with Amazon SageMaker Data Wrangler

Amazon SageMaker Data Wrangler is a new capability of Amazon SageMaker that makes it faster for data scientists and engineers to prepare data for machine learning (ML) applications via a visual interface. Data preparation is a crucial step of the ML lifecycle, and Data Wrangler provides an end-to-end solution to import, prepare, transform, featurize, and […]

Run AutoML experiments with large parquet datasets using Amazon SageMaker Autopilot

Starting today, you can use Amazon SageMaker Autopilot to tackle regression and classification tasks on large datasets up to 100 GB. Additionally, you can now provide your datasets in either CSV or Apache Parquet content types. Businesses are generating more data than ever. A corresponding demand is growing for generating insights from these large datasets […]

How Logz.io accelerates ML recommendations and anomaly detection solutions with Amazon SageMaker

Logz.io is an AWS Partner Network (APN) Advanced Technology Partner with AWS Competencies in DevOps, Security, and Data & Analytics. Logz.io offers a software as a service (SaaS) observability platform based on best-in-class open-source software solutions for log, metric, and tracing analytics. Customers are sending an increasing amount of data to Logz.io from various data […]

Distributed fine-tuning of a BERT Large model for a Question-Answering Task using Hugging Face Transformers on Amazon SageMaker

From training new models to deploying them in production, Amazon SageMaker offers the most complete set of tools for startups and enterprises to harness the power of machine learning (ML) and Deep Learning. With its Transformers open-source library and ML platform, Hugging Face makes transfer learning and the latest ML models accessible to the global […]

Detect NLP data drift using custom Amazon SageMaker Model Monitor

Natural language understanding is applied in a wide range of use cases, from chatbots and virtual assistants, to machine translation and text summarization. To ensure that these applications are running at an expected level of performance, it’s important that data in the training and production environments is from the same distribution. When the data that […]

Label text for aspect-based sentiment analysis using SageMaker Ground Truth

This blog post was last reviewed and updated August, 2022 with revised sample document links. The Amazon Machine Learning Solutions Lab (MLSL) recently created a tool for annotating text with named-entity recognition (NER) and relationship labels using Amazon SageMaker Ground Truth. Annotators use this tool to label text with named entities and link their relationships, thereby […]