Category: Amazon SageMaker JumpStart

Organizations across industries such as retail, banking, finance, healthcare, manufacturing, and lending often have to deal with vast amounts of unstructured text documents coming from various sources, such as news, blogs, product reviews, customer support channels, and social media. These documents contain critical information that’s key to making important business decisions. As an organization grows, […]

July 2023: This post was reviewed for accuracy. Today, we announce the public availability of Amazon’s state-of-the-art Alexa Teacher Model with 20 billion parameters  (AlexaTM 20B) through Amazon SageMaker JumpStart, SageMaker’s machine learning hub. AlexaTM 20B is a multilingual large-scale sequence-to-sequence (seq2seq) language model developed by Amazon. You can use AlexaTM 20B for a wide […]

Image classification is a computer vision-based machine learning (ML) technique that allows you to classify images. Some well-known examples of image classification include classifying handwritten digits, medical image classification, and facial recognition. Image classification is a useful technique with several business applications, but building a good image classification model isn’t trivial. Several considerations can play […]

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, and is composed of tumors with significant molecular heterogeneity resulting from differences in intrinsic oncogenic signaling pathways [1]. Enabling precision medicine, anticipating patient preferences, detecting disease, and improving care quality for NSCLC patients are important topics among healthcare and life sciences (HCLS) […]

March 2023: This post was reviewed and updated with support for Stable Diffusion inpainting model. Today, we announce that Stable Diffusion 1 and Stable Diffusion 2 are available in Amazon SageMaker JumpStart. JumpStart is the machine learning (ML) hub of SageMaker that provides hundreds of built-in algorithms, pre-trained models, and end-to-end solution templates to help you quickly get started with […]

Today, we announce that large language models Bloom and GPT-2 are available in SageMaker JumpStart. Amazon SageMaker JumpStart is the machine learning hub of SageMaker that provides hundreds of built-in algorithms, pre-trained models, and end-to-end solution templates to help customers quickly get started with machine learning (ML). You can use these models for a wide […]

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 […]

Businesses can lose billions of dollars each year due to malicious users and fraudulent transactions. As more and more business operations move online, fraud and abuses in online systems are also on the rise. To combat online fraud, many businesses have been using rule-based fraud detection systems. However, traditional fraud detection systems rely on a […]

To train a machine learning (ML) model, you need a large, high-quality, labeled dataset. Amazon SageMaker Ground Truth helps you build high-quality training datasets for your ML models. With Ground Truth, you can use workers from either Amazon Mechanical Turk, a vendor company of your choosing, or an internal, private workforce to enable you to […]

Amazon SageMaker JumpStart solutions are a feature within Amazon SageMaker Studio that allow a simple-click experience to set up your own machine learning (ML) workflows. When you launch a solution, various of AWS resources are set up in your account to demonstrate how the business problem can be solved using the pre-built architecture. The solutions […]