Tag: Veliswa Boya

The AWS User Group Japan (JAWS-UG) hosted JAWS PANKRATION 2024 themed ‘No Border’. This is a 24-hour online event where AWS Heroes, AWS Community Builders, AWS User Group leaders, and others from around the world discuss topics ranging from cultural discussions to technical talks. One of the speakers at this event, Kevin Tuei, an AWS Community Builder based in Kenya, highlighted the importance of building in public and sharing your knowledge with others, a very fitting talk for this kind of event. Last week’s launches Here are some launches that got my attention during the previous week. Amazon S3 now supports conditional writes – We’ve added support for conditional writes in Amazon S3 which check for existence of an object before…

Today, we are announcing the general availability of Amazon Marketing Cloud (AMC) on AWS Clean Rooms to help advertisers use their first-party signals to collaborate with Amazon Ads unique signals. With this collaboration, advertisers can generate differentiated insights, discover new audiences, and enable advertising campaign planning, activation, and measurement use cases, all without having to move their underlying signals outside of their AWS account. With AMC on AWS Clean Rooms, customers can easily prepare their data, match and create audiences, use custom insights to activate more relevant advertising campaigns with Amazon Ads, and measure return on ad spend. All of this can be accomplished from the most secure cloud computing environment available today. Advertisers continually strive to reach new audiences…

Today, we announce the general availability of data preparation authoring in AWS Glue Studio Visual ETL. This is a new no-code data preparation user experience for business users and data analysts with a spreadsheet-style UI that runs data integration jobs at scale on AWS Glue for Spark. The new visual data preparation experience makes it easier for data analysts and data scientists to clean and transform data to prepare it for analytics and machine learning (ML). Within this new experience, you can choose from hundreds of pre-built transformations to automate data preparation tasks, all without the need to write any code. Business analysts can now collaborate with data engineers to build data integration jobs. Data engineers can use the Glue…

Today, we are thrilled to announce the general availability of a fully managed MLflow capability on Amazon SageMaker. MLflow, a widely-used open-source tool, plays a crucial role in helping machine learning (ML) teams manage the entire ML lifecycle. With this new launch, customers can now effortlessly set up and manage MLflow Tracking Servers with just a few steps, streamlining the process and boosting productivity. Data Scientists and ML developers can leverage MLflow to track multiple attempts at training models as runs within experiments, compare these runs with visualizations, evaluate models, and register the best models to a Model Registry. Amazon SageMaker eliminates the undifferentiated heavy lifting required to set up and manage MLflow, providing ML administrators with a quick and…