Category: Amazon SageMaker

March 2023: This post was reviewed and updated to comply with service version update.. RStudio on Amazon SageMaker is the industry’s first fully managed RStudio Workbench in cloud. You can quickly launch the familiar RStudio integrated development environment (IDE), and dial up and down the underlying compute resources without interrupting your work, making it easy […]

Online conversations are ubiquitous in modern life, spanning industries from video games to telecommunications. This has led to an exponential growth in the amount of online conversation data, which has helped in the development of state-of-the-art natural language processing (NLP) systems like chatbots and natural language generation (NLG) models. Over time, various NLP techniques for […]

Large attention-based transformer models have obtained massive gains on natural language processing (NLP). However, training these gigantic networks from scratch requires a tremendous amount of data and compute. For smaller NLP datasets, a simple yet effective strategy is to use a pre-trained transformer, usually trained in an unsupervised fashion on very large datasets, and fine-tune […]

July 2023: You can also use the newly launched JumpStart APIs, an extension of the SageMaker Python SDK. These APIs allow you to programmatically deploy and fine-tune a vast selection of JumpStart-supported pre-trained models on your own datasets. Please refer to Amazon SageMaker JumpStart models and algorithms now available via API for more details on how […]

In computer vision, semantic segmentation is the task of classifying every pixel in an image with a class from a known set of labels such that pixels with the same label share certain characteristics. It generates a segmentation mask of the input images. For example, the following images show a segmentation mask of the cat […]

Every business needs the ability to predict the future accurately in order to make better decisions and give the company a competitive advantage. With historical data, businesses can understand trends, make predictions of what might happen and when, and incorporate that information into their future plans, from product demand to inventory planning and staffing. If […]

Launched at AWS re:Invent 2021, Amazon SageMaker Ground Truth Plus helps you create high-quality training datasets by removing the undifferentiated heavy lifting associated with building data labeling applications and managing the labeling workforce. All you do is share data along with labeling requirements, and Ground Truth Plus sets up and manages your data labeling workflow […]

July 2023: This post was reviewed for accuracy. This post is co-written with Thomas Capelle at Weights & Biases. As more organizations use deep learning techniques such as computer vision and natural language processing, the machine learning (ML) developer persona needs scalable tooling around experiment tracking, lineage, and collaboration. Experiment tracking includes metadata such as […]

This blog post is co-authored by Guillermo Ribeiro, Sr. Data Scientist at Cepsa. Machine learning (ML) has rapidly evolved from being a fashionable trend emerging from academic environments and innovation departments to becoming a key means to deliver value across businesses in every industry. This transition from experiments in laboratories to solving real-world problems in […]

As enterprise businesses embrace machine learning (ML) across their organizations, manual workflows for building, training, and deploying ML models tend to become bottlenecks to innovation. To overcome this, enterprises needs to shape a clear operating model defining how multiple personas, such as data scientists, data engineers, ML engineers, IT, and business stakeholders, should collaborate and […]