The DynamoDB paper - Marc's Blog
About Me My name is Marc Brooker. I've been writing code, reading code, and living vicariously through computers for as long as I can remember. I like to build things that work. I also dabble in machining, welding, cooking and skiing. I'm currently an engineer at Amazon Web Services (AWS) in Seattle, where I work on databases, serverless, and serverless databases. Before that, I worked on EC2 and
A Second Conversation with Werner Vogels – Communications of the ACM
CACM Web Account Membership in ACM includes a subscription to Communications of the ACM (CACM), the computing industry's most trusted source for staying connected to the world of advanced computing. Sign In Sign Up When I joined Amazon in 1998, the company had a single U.S.-based website selling only books and running a monolithic C application on five servers, a handful of Berkeley DBs for key/va
Millions of tiny databases
As a Senior Scientist at AWS AI/ML leading the Personalization and Privacy AI teams, you will have deep subject matter expertise in the areas of recommender systems, personalization, generative AI and privacy. You will provide thought leadership on and lead strategic efforts in the personalization of models to be used by customer applications across a wide range of customer use cases. Particular n
Test data quality at scale with Deequ | Amazon Web Services
AWS Big Data Blog Test data quality at scale with Deequ March 2023: You can now use AWS Glue Data Quality to measure and manage the quality of your data. AWS Glue Data Quality is built on DeeQu and it offers a simplified user experience for customers who want to this open-source package. Refer to the blog and documentation for additional details. You generally write unit tests for your code, but d
Visual Search at Pinterest
We demonstrate that, with the availability of distributed computation platforms such as Amazon Web Services and open-source tools, it is possible for a small engineering team to build, launch and maintain a cost-effective, large-scale visual search system with widely available tools. We also demonstrate, through a comprehensive set of live experiments at Pinterest, that content recommendation powe
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GluonTS: Probabilistic and Neural Time Series Modeling in Python
GitHub - awslabs/gluonts: Probabilistic time series modeling in Python
Intermittent Demand Forecasting with Renewal Processes
Amazon SageMaker autopilot: a white box AutoML solution at scale
End-to-end benchmarking of deep learning platforms
Efficient Knowledge Graph Accuracy Evaluation
Cloud and systems
Use of Formal Methods at Amazon Web Services