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Compiling Quantum Circuits for Dynamically Field-Programmable Neutral Atoms Array Processors

Daniel Bochen Tan1, Dolev Bluvstein2, Mikhail D. Lukin2, and Jason Cong11Computer Science Department, University of California, Los Angeles, CA 900952Department of Physics, Harvard University,...

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Train and deploy ML models in a multicloud environment using Amazon SageMaker | Amazon Web Services

As customers accelerate their migrations to the cloud and transform their business, some find themselves in situations where they have to manage IT operations...

Run multiple generative AI models on GPU using Amazon SageMaker multi-model endpoints with TorchServe and save up to 75% in inference costs | Amazon...

Multi-model endpoints (MMEs) are a powerful feature of Amazon SageMaker designed to simplify the deployment and operation of machine learning (ML) models. With MMEs,...

Handling Duplicate Values in a Pandas DataFrame

IntroductionAs a data analyst, it is our responsibility to ensure data integrity to obtain accurate and trustworthy insights. Data cleansing plays a vital role...

Get started with the open-source Amazon SageMaker Distribution | Amazon Web Services

Data scientists need a consistent and reproducible environment for machine learning (ML) and data science workloads that enables managing dependencies and is secure. AWS...

Bias-tailored quantum LDPC codes

Joschka Roffe1,2, Lawrence Z. Cohen3, Armanda O. Quintavalle2,4, Daryus Chandra5, and Earl T. Campbell2,4,61Dahlem Center for Complex Quantum Systems, Freie Universität Berlin, 14195 Berlin,...

Schedule your notebooks from any JupyterLab environment using the Amazon SageMaker JupyterLab extension | Amazon Web Services

Jupyter notebooks are highly favored by data scientists for their ability to interactively process data, build ML models, and test these models by making...

Implementing Other SVM Flavors with Python’s Scikit-Learn

IntroductionThis guide is the third and final part of three guides about Support Vector Machines (SVMs). In this guide, we will keep working with...

Implementing SVM and Kernel SVM with Python’s Scikit-Learn

IntroductionThis guide is the first part of three guides about Support Vector Machines (SVMs). In this series, we will work on a forged bank...

DBSCAN with Scikit-Learn in Python

IntroductionYou are working in a consulting company as a data scientis. The project you were currently assigned to has data from students who have...

Hosting YOLOv8 PyTorch models on Amazon SageMaker Endpoints

Deploying models at scale can be a cumbersome task for many data scientists and machine learning engineers. However, Amazon SageMaker endpoints provide a simple...

Training Neural Radiance Field (NeRF) Models with Keras/TensorFlow and DeepVision

Neural Radiance Fields, colloquially known as NeRFs have struck the world by storm in 2020, released alongside the paper "NeRF: Representing Scenes as Neural...

Virtual fashion styling with generative AI using Amazon SageMaker 

The fashion industry is a highly lucrative business, with an estimated value of $2.1 trillion by 2025, as reported by the World Bank. This...

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