A deep learning model in its simplest form are layers of perceptrons connected in tandem. Without any activation functions, they are just matrix multiplications with limited power, regardless how many of them. Activation is the magic why neural network can be an approximation to… Read More »Using Activation Functions in Deep Learning Models Adrian Tam MachineLearningMastery.com
Everybody knows about ChatGPT. And everybody knows about ChatGPT’s propensity to “make up” facts and details when it needs to, a phenomenon that’s come to be called “hallucination.” And everyone has seen arguments that this will bring about the end of civilization as we… Read More »AI Hallucinations: A Provocation Mike Loukides AI & ML – Radar
RAID, or Redundant Array of Independent Disks, is a technology that helps protect against the loss of data in case one disk fails by providing redundancy through multiple disks. While there are many different types of RAID configurations available, it’s important to understand which… Read More »A Guide to Using RAID for Database Servers Seb Programmathically
This post is co-written by Zdenko Estok, Cloud Architect at Accenture and Sakar Selimcan, DeepRacer SME at Accenture. With the increasing use of artificial intelligence (AI) and machine learning (ML) for a vast majority of industries (ranging from healthcare to insurance, from manufacturing to… Read More »Configure an AWS DeepRacer environment for training and log analysis using the AWS CDK Zdenko Estok AWS Machine Learning Blog
This paper was accepted at the Workshops on Data Science with Human in the Loop at EMNLP 2022 Identifying and integrating missing facts is a crucial task for knowledge graph completion to ensure robustness towards downstream applications such as question answering. Adding new facts to… Read More »Improving Human Annotation Effectiveness for Fact Collection by Identifying the Most Relevant Answers Apple Machine Learning Research
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
A deep learning model is a mathematical abstraction of data, in which a lot of parameters are involved. Training these parameters can take hours, days, and even weeks but afterward, you can make use of the result to apply on new data. This is… Read More »Save and Load Your PyTorch Models Adrian Tam MachineLearningMastery.com
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