Category: Amazon SageMaker

This post is co-authored with Piotr Klesta, Robert Meisner and Lukasz Luszczynski of ERGO Artificial intelligence (AI) and related technologies are already finding applications in our homes, cars, industries, and offices. The insurance business is no exception to this. When AI is implemented correctly, it adds a major competitive advantage. It enhances the decision-making process, […]

Since the 2008 financial crisis, banking supervisory institutions such as the Basel Committee on Banking Supervision (BCBS) have strengthened regulations. There is now increased oversight over the financial services industry. For banks, making the necessary changes to comply with these rules is a challenging, multi-year effort. Basel IV, a massive update to existing rules, is […]

This post was co-written by Amr Ragab, AWS Sr. Solutions Architect, EC2 Engineering and Anant Nawalgaria, former AWS Professional Services EMEA. One of the most common needs we have heard from customers in Autonomous Vehicle (AV) development, is to launch a hybrid deployment environment at scale. As vehicle fleets are deployed across the globe, they […]

Many organizations are moving their data from silos and aggregating it in one location. Collecting this data in a data lake enables you to perform analytics and machine learning on that data. You can store your data in purpose-built data stores, like a data warehouse, to get quick results for complex queries on structured data. […]

This post was co-written with Marcus Rosen, a Principal  – Machine Learning Operations with Rio Tinto, a global mining company.  Data pre-processing is an important step in setting up Machine Learning (ML) projects for success. Many AWS customers use Apache Spark on AWS Glue or Amazon EMR to run data pre-processing scripts while using Amazon SageMaker […]

For decades, enterprises used online analytical processing (OLAP) workloads to answer complex questions about their business by filtering and aggregating their data. These complex queries were compute and memory-intensive. This required teams to build and maintain complex extract, transform, and load (ETL) pipelines to model and organize data, oftentimes with commercial-grade analytics tools. In this […]

Research organizations across industry verticals have unique needs. These include facilitating stakeholder collaboration, setting up compute environments for experimentation, handling large datasets, and more. In essence, researchers want the freedom to focus on their research, without the undifferentiated heavy-lifting of managing their environments. In this blog, I show you how to set up a managed […]

In the blog, Redacting Personal Data from Connected Cars Using Amazon Rekognition, we demonstrated how you can redact personal data such as human faces using Amazon Rekognition. Traversing the video, frame by frame, and identifying personal information in each frame takes time. This solution is great for small video clips, where you do not need […]

This post was co-written by Louis Lim, a manager in Accenture AWS Business Group, and Soheil Moosavi, a data scientist consultant in Accenture Applied Intelligence (AAI) team. Virtually every electric customer in the US and Canada has, at one time or another, experienced a sustained electric outage as a direct result of a tree and […]

This post was co-written by Michael Wirig, Software Engineering Manager at Grōv Technologies. A substantial percentage of the world’s habitable land is used for livestock farming for dairy and meat production. The dairy industry has leveraged technology to gain insights that have led to drastic improvements and are continuing to accelerate. A gallon of milk […]