Tag: Numpy
Automate Amazon SageMaker Pipelines DAG creation | Amazon Web Services
Creating scalable and efficient machine learning (ML) pipelines is crucial for streamlining the development, deployment, and management of ML models. In this post, we...
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Qibolab: an open-source hybrid quantum operating system
Stavros Efthymiou1, Alvaro Orgaz-Fuertes1, Rodolfo Carobene2,3,1, Juan Cereijo1,4, Andrea Pasquale1,5,6, Sergi Ramos-Calderer1,4, Simone Bordoni1,7,8, David Fuentes-Ruiz1, Alessandro Candido5,6,9, Edoardo Pedicillo1,5,6, Matteo Robbiati5,9, Yuanzheng Paul...
How HSR.health is limiting risks of disease spillover from animals to humans using Amazon SageMaker geospatial capabilities | Amazon Web Services
This is a guest post co-authored by Ajay K Gupta, Jean Felipe Teotonio and Paul A Churchyard from HSR.health. HSR.health is a geospatial health...
Train and host a computer vision model for tampering detection on Amazon SageMaker: Part 2 | Amazon Web Services
In the first part of this three-part series, we presented a solution that demonstrates how you can automate detecting document tampering and fraud at...
Selenium Python: Mastering Frame and Window Management for Efficient Web Automation – PrimaFelicitas
Modern web applications have revolutionized a lot since their initial introduction. For instance, modern applications can function seamlessly on multiple devices like desktops, tablets,...
Mitigate hallucinations through Retrieval Augmented Generation using Pinecone vector database & Llama-2 from Amazon SageMaker JumpStart | Amazon Web Services
Despite the seemingly unstoppable adoption of LLMs across industries, they are one component of a broader technology ecosystem that is powering the new AI...
Package and deploy classical ML and LLMs easily with Amazon SageMaker, part 1: PySDK Improvements | Amazon Web Services
Amazon SageMaker is a fully managed service that enables developers and data scientists to quickly and effortlessly build, train, and deploy machine learning (ML)...
Amazon EC2 DL2q instance for cost-efficient, high-performance AI inference is now generally available | Amazon Web Services
This is a guest post by A.K Roy from Qualcomm AI. Amazon Elastic Compute Cloud (Amazon EC2) DL2q instances, powered by Qualcomm AI 100...
Geospatial generative AI with Amazon Bedrock and Amazon Location Service | Amazon Web Services
Today, geospatial workflows typically consist of loading data, transforming it, and then producing visual insights like maps, text, or charts. Generative AI can automate...
Abstraqt: Analysis of Quantum Circuits via Abstract Stabilizer Simulation
Benjamin Bichsel, Anouk Paradis, Maximilian Baader, and Martin VechevETH Zurich, SwitzerlandFind this paper interesting or want to discuss? Scite or leave a comment on...
Fine-tune Whisper models on Amazon SageMaker with LoRA | Amazon Web Services
Whisper is an Automatic Speech Recognition (ASR) model that has been trained using 680,000 hours of supervised data from the web, encompassing a range...
Implement a custom AutoML job using pre-selected algorithms in Amazon SageMaker Automatic Model Tuning | Amazon Web Services
AutoML allows you to derive rapid, general insights from your data right at the beginning of a machine learning (ML) project lifecycle. Understanding up...
Guide to Hash Tables in Python
IntroductionHash tables offer an efficient and flexible method of storing and retrieving data, making them indispensable for tasks involving large data sets or requiring...