zetabyte

​ Table of Contents Building a Dataset for Triplet Loss with Keras and TensorFlow Labeled Faces in the Wild Dataset Configuring Your Development Environment Having Problems Configuring Your Development Environment? Project Structure Creating Our Configuration File Creating Our Data Pipeline Preprocessing Faces: Detection and Cropping… Read More »Building a Dataset for Triplet Loss with Keras and TensorFlow Shivam Chandhok PyImageSearch

​Posted by Vahab Mirrokni, VP and Google Fellow, Google Research (This is Part 5 in our series of posts covering different topical areas of research at Google. You can find other posts in the series here.) Robust algorithm design is the backbone of systems across… Read More »Google Research, 2022 & beyond: Algorithmic advances Google AI Google AI Blog

​ This post is co-written with Jonathan Jung, Mike Band, Michael Chi, and Thompson Bliss at the National Football League. A coverage scheme refers to the rules and responsibilities of each football defender tasked with stopping an offensive pass. It is at the core of… Read More »Identifying defense coverage schemes in NFL’s Next Gen Stats Huan Song AWS Machine Learning Blog

​ Amazon Textract is a machine learning (ML) service that automatically extracts text, handwriting, and data from any document or image. AnalyzeDocument Signatures is a feature within Amazon Textract that offers the ability to automatically detect signatures on any document. This can reduce the need… Read More »Detect signatures on documents or images using the signatures feature in Amazon Textract Maran Chandrasekaran AWS Machine Learning Blog

​ Earth’s changing climate poses an increased risk of drought due to global warming. Since 1880, the global temperature has increased 1.01 °C. Since 1993, sea levels have risen 102.5 millimeters. Since 2002, the land ice sheets in Antarctica have been losing mass at a… Read More »Monitoring Lake Mead drought using the new Amazon SageMaker geospatial capabilities Xiong Zhou AWS Machine Learning Blog

​Posted by Ted White and Ofer Naaman, Staff Research Scientists, Google Quantum AI The Google Quantum AI team is building quantum computers with superconducting microwave circuits, but much like a classical computer the superconducting processor at the heart of these computers is only part of… Read More »Amplification at the quantum limit Google AI Google AI Blog

​ Machine learning (ML) has become ubiquitous. Our customers are employing ML in every aspect of their business, including the products and services they build, and for drawing insights about their customers. To build an ML-based application, you have to first build the ML model… Read More »Optimize your machine learning deployments with auto scaling on Amazon SageMaker Mohan Gandhi AWS Machine Learning Blog

​Posted by Jinsung Yoon and Sercan O. Arik, Research Scientists, Google Research, Cloud AI Team Anomaly detection (AD), the task of distinguishing anomalies from normal data, plays a vital role in many real-world applications, such as detecting faulty products from vision sensors in manufacturing, fraudulent… Read More »Unsupervised and semi-supervised anomaly detection with data-centric ML Google AI Google AI Blog