AWS Architecture Blog
Category: HAQM Machine Learning
Top Architecture Blog Posts of 2023
2023 was a rollercoaster year in tech, and we at the AWS Architecture Blog feel so fortunate to have shared in the excitement. As we move into 2024 and all of the new technologies we could see, we want to take a moment to highlight the brightest stars from 2023. As always, thanks to our […]
Introducing the latest Machine Learning Lens for the AWS Well-Architected Framework
Today, we are delighted to introduce the latest version of the AWS Well-Architected Machine Learning (ML) Lens whitepaper. The AWS Well-Architected Framework provides architectural best practices for designing and operating ML workloads on AWS. It is based on six pillars: Operational Excellence, Security, Reliability, Performance Efficiency, Cost Optimization, and—a new addition to this revision—Sustainability. The […]
Optimizing data with automated intelligent document processing solutions
Many organizations struggle to effectively manage and derive insights from the large amount of unstructured data locked in emails, PDFs, images, scanned documents, and more. The variety of formats, document layouts, and text makes it difficult for any standard Optical Character Recognition (OCR) to extract key insights from these data sources. To help organizations overcome […]
Detecting solar panel damage with HAQM Rekognition Custom Labels
Enterprises perform quality control to ensure products meet production standards and avoid potential brand reputation damage. As the cost of sensors decreases and connectivity increases, industries adopt real-time imagery analysis to detect quality issues. At the same time, artificial intelligence (AI) advancements enable advanced automation, reduce overall cost and project time, and produce accurate defect […]
Introducing the new AWS Well-Architected Machine Learning Lens
The AWS Well-Architected Framework provides you with a formal approach to compare your workloads against best practices. It also includes guidance on how to make improvements. Machine learning (ML) algorithms discover and learn patterns in data, and construct mathematical models to predict future data. These solutions can revolutionize lives through better diagnoses of diseases, environmental […]
Field Notes: Build a Cross-Validation Machine Learning Model Pipeline at Scale with HAQM SageMaker
When building a machine learning algorithm, such as a regression or classification algorithm, a common goal is to produce a generalized model. This is so that it performs well on new data that the model has not seen before. Overfitting and underfitting are two fundamental causes of poor performance for machine learning models. A model […]
Classifying Millions of HAQM items with Machine Learning, Part I: Event Driven Architecture
As part of AWS Professional Services, we work with customers across different industries to understand their needs and supplement their teams with specialized skills and experience. Some of our customers are internal teams from the HAQM retail organization who request our help with their initiatives. One of these teams, the Global Environmental Affairs team, identifies […]
Improving Retail Forecast Accuracy with Machine Learning
The global retail market continues to grow larger and the influx of consumer data increases daily. The rise in volume, variety, and velocity of data poses challenges with demand forecasting and inventory planning. Outdated systems generate inaccurate demand forecasts. This results in multiple challenges for retailers. They are faced with over-stocking and lost sales, and […]
Integrating Redaction of FinServ Data into a Machine Learning Pipeline
Financial companies process hundreds of thousands of documents every day. These include loan and mortgage statements that contain large amounts of confidential customer information. Data privacy requires that sensitive data be redacted to protect the customer and the institution. Redacting digital and physical documents is time-consuming and labor-intensive. The accidental or inadvertent release of personal information […]
Field Notes: Automating Data Ingestion and Labeling for Autonomous Vehicle Development
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 […]