AWS Machine Learning Blog

Category: Artificial Intelligence

AWS Announces the global expansion of AWS CCI Solutions

We’re excited to announce the global availability of AWS Contact Center Intelligence (AWS CCI) solutions powered by AWS AI Services and made available through the AWS Partner Network. AWS CCI solutions enable you to leverage AWS machine learning (ML) capabilities with your current contact center provider to gain greater efficiencies and deliver increasingly tailored customer […]

Read More
The following diagram illustrates this architecture.

Hosting a private PyPI server for Amazon SageMaker Studio notebooks in a VPC

Amazon SageMaker Studio notebooks provide a full-featured integrated development environment (IDE) for flexible machine learning (ML) experimentation and development. Security measures secure and support a versatile and collaborative environment. In some cases, such as to protect sensitive data or meet regulatory requirements, security protocols require that public internet access be disabled in the development environment. […]

Read More

Artificial intelligence and machine learning continues at AWS re:Invent

A fresh new year is here, and we wish you all a wonderful 2021. We signed off last year at AWS re:Invent on the artificial intelligence (AI) and machine learning (ML) track with the first ever machine learning keynote and over 50 AI/ML focused technical sessions covering industries, use cases, applications, and more. You can […]

Read More

Accelerating MLOps at Bayer Crop Science with Kubeflow Pipelines and Amazon SageMaker

This is a guest post by the data science team at Bayer Crop Science.  Farmers have always collected and evaluated a large amount of data with each growing season: seeds planted, crop protection inputs applied, crops harvested, and much more. The rise of data science and digital technologies provides farmers with a wealth of new […]

Read More

Implementing a custom labeling GUI with built-in processing logic with Amazon SageMaker Ground Truth

Amazon SageMaker Ground Truth is a fully managed data labeling service that makes it easy to build highly accurate training datasets for machine learning. It offers easy access to Amazon Mechanical Turk and private human labelers, and provides them with built-in workflows and interfaces for common labeling tasks. A labeling team may wish to use […]

Read More
The following diagram illustrates our solution architecture.

Building a secure search application with access controls using Amazon Kendra

For many enterprises, critical business information is often stored as unstructured data scattered across multiple content repositories. Not only is it challenging for organizations to make this information available to employees when they need it, but it’s also difficult to do so securely so relevant information is available to the right employees or employee groups. […]

Read More

Extracting buildings and roads from AWS Open Data using Amazon SageMaker

Sharing data and computing in the cloud allows data users to focus on data analysis rather than data access. Open Data on AWS helps you discover and share public open datasets in the cloud. The Registry of Open Data on AWS hosts a large amount of public open data. The datasets range from genomics to climate to transportation […]

Read More

How an important change in web standards impacts your image annotation jobs

Earlier in 2020, widely used browsers like Chrome and Firefox changed their default behavior for rotating images based on image metadata, referred to as EXIF data. Previously, images always displayed in browsers exactly how they’re stored on disk, which is typically unrotated. After the change, images now rotate according to a piece of image metadata […]

Read More

How Foxconn built an end-to-end forecasting solution in two months with Amazon Forecast

This is a guest post by Foxconn. The content and opinions in this post are those of the third-party author and AWS is not responsible for the content or accuracy of this post.  In their own words, “Established in Taiwan in 1974, Hon Hai Technology Group (Foxconn) is the world’s largest electronics manufacturer. Foxconn is […]

Read More
For an existing data lake registered with Lake Formation, the following diagram illustrates the proposed implementation.

Control and audit data exploration activities with Amazon SageMaker Studio and AWS Lake Formation

Certain industries are required to audit all access to their data. This includes auditing exploratory activities performed by data scientists, who usually query data from within machine learning (ML) notebooks. This post walks you through the steps to implement access control and auditing capabilities on a per-user basis, using Amazon SageMaker Studio notebooks and AWS […]

Read More