AWS Machine Learning Blog
Category: Artificial Intelligence
Increase your machine learning success with AWS ML services and AWS Machine Learning Embark
This is a guest post from Mikael Graindorge, Sales Operations Leader at Thermo Fisher Scientific. In the life sciences industry, data is growing in abundance and is getting increasingly complex, which makes it challenging to use traditional analytics methodologies. At Thermo Fisher Scientific, our mission is to make the world healthier, cleaner, and safer, and […]
Fine-tune and host Hugging Face BERT models on Amazon SageMaker
The last few years have seen the rise of transformer deep learning architectures to build natural language processing (NLP) model families. The adaptations of the transformer architecture in models such as BERT, RoBERTa, T5, GPT-2, and DistilBERT outperform previous NLP models on a wide range of tasks, such as text classification, question answering, summarization, and […]
Dive deep into Amazon SageMaker Studio Notebooks architecture
Machine learning (ML) is highly iterative and complex in nature, and requires data scientists to explore multiple ways in which a business problem can be solved. Data scientists have to use tools that support interactive experimentation so you can run code, review its outputs, and annotate it, which makes it easy to work and collaborate […]
Meet Aria, the first New Zealand English accented voice for Amazon Polly – includes limited te reo Māori support
We are excited to announce Aria, Amazon Polly’s first New Zealand English Neural text-to-speech (NTTS) voice. Similar to other Amazon Polly voices, Aria is developed as a voice that sounds bright, natural, and upbeat. This new voice for Aotearoa (New Zealand in Māori) is uniquely Kiwi. It includes a number of common te reo Māori […]
Enable scalable, highly accurate, and cost-effective video analytics with Axis Communications and Amazon Rekognition
With the number of cameras and sensors deployed growing exponentially, companies across industries are consuming more video than ever before. Additionally, advancements in analytics have expanded potential use cases, and these devices are now used to improve business operations and intelligence. In turn, the ability to effectively process video at these rapidly expanding volumes is […]
Recognize celebrities in images and videos using Amazon Rekognition
The celebrity recognition feature in Amazon Rekognition automatically recognizes tens of thousands of well-known personalities in images and videos using machine learning (ML). Celebrity recognition significantly reduces the repetitive manual effort required to tag produced media content and make it readily searchable. Starting today, we’re updating our models to provide higher accuracy (lower false detections […]
Use a SageMaker Pipeline Lambda step for lightweight model deployments
With Amazon SageMaker Pipelines, you can create, automate, and manage end-to-end machine learning (ML) workflows at scale. SageMaker Projects build on SageMaker Pipelines by providing several MLOps templates that automate model building and deployment pipelines using continuous integration and continuous delivery (CI/CD). To help you get started, SageMaker Pipelines provides many predefined step types, such […]
Access an Amazon SageMaker Studio notebook from a corporate network
Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning. It provides a single, web-based visual interface where you can perform all ML development steps required to build, train, and deploy models. You can quickly upload data, create new notebooks, train and tune models, move back and forth between steps to […]
Build conversation flows with multi-valued slots in Amazon Lex
Multiple pieces of information are often required to complete a task or to process a query. For example, when talking to an insurance agent, a caller might ask, “Can you provide me quotes for home, auto, and boat?” The agent recognizes this as a list of policy types before continuing with the conversation. Automation of […]
Migrate your work to an Amazon SageMaker notebook instance with Amazon Linux 2
Amazon SageMaker notebook instances now support Amazon Linux 2, so you can now create a new Amazon SageMaker notebook instance to start developing your machine learning (ML) models with the latest updates. An obvious question is: what do I need to do to migrate my work from an existing notebook instance that runs on Amazon […]