AWS Machine Learning Blog

OCTOBER 16, 2023

These models range from lightweight tree-based models to deep learning computer vision models, which need to run on GPUs to achieve low latency and improve the user experience. This approach was initially used for all company services, including microservices that run expensive computer vision ML models.

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AWS Machine Learning Blog

OCTOBER 2, 2023

In this series, we walk you through the process of architecting and building an integrated end-to-end MLOps pipeline for a computer vision use case at the edge using SageMaker, AWS IoT Greengrass, and the AWS Cloud Development Kit (AWS CDK). The following diagram illustrates what this could look like for our computer vision pipeline.

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AWS Machine Learning Blog

DECEMBER 1, 2023

She has a decade of experience in DevOps, infrastructure, and ML. She is also the author of a book on computer vision. In his spare time, he loves traveling and writing. Lauren Mullennex is a Senior AI/ML Specialist Solutions Architect at AWS. In her spare time, she enjoys traveling and hiking.

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AWS Machine Learning Blog

AUGUST 26, 2024

To facilitate computer vision-based sign language recognition, the dataset also includes numeric ID labels for sign variants, video sequences in uncompressed raw format, and camera calibration sequences. We can call the Amazon Bedrock API directly from the Step Functions workflow to save on Lambda compute cost.

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AWS Machine Learning Blog

JUNE 27, 2023

Earth.com’s leadership team recognized the vast potential of EarthSnap and set out to create an application that utilizes the latest deep learning (DL) architectures for computer vision (CV). That is where Provectus , an AWS Premier Consulting Partner with competencies in Machine Learning, Data & Analytics, and DevOps, stepped in.

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AWS Machine Learning Blog

FEBRUARY 1, 2024

She has a diverse background, having worked in many technical disciplines, including software development, agile leadership, and DevOps, and is an advocate for women in tech. He holds an MSEE from the University of Michigan, where he worked on computer vision for autonomous vehicles.

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AWS Machine Learning Blog

SEPTEMBER 23, 2024

James’s work covers a wide range of ML use cases, with a primary interest in computer vision, deep learning, and scaling ML across the enterprise. She has a decade of experience in DevOps, infrastructure, and ML. Her areas of focus include computer vision, MLOps/LLMOps, and generative AI. Shibin Michaelraj is a Sr.

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AWS Machine Learning Blog

MARCH 30, 2023

ML model optimized for annotators A tremendous number of high-performing object detection models have been proposed by the computer vision community in recent years. However, these state-of-the-art models are typically optimized for unguided object detection.

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Chatbots Life

MAY 16, 2023

Services : Mobile app development, web development, blockchain technology implementation, 360′ design services, DevOps, OpenAI integrations, machine learning, and MLOps. Services : AI Solution Development, ML Engineering, Data Science Consulting, NLP, AI Model Development, AI Strategic Consulting, Computer Vision.

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Mlearning.ai

APRIL 24, 2023

GitHub is useful, in comparison to DevOps Pipeline, because many people can work on the project using branches; new changes can be automatically ran and tracked using versioning. You can monitor and make changes to the deployed model using the three areas in the DevOps platform.

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AWS Machine Learning Blog

MAY 31, 2024

His area of focus is AI for DevOps and machine learning. He holds a Bachelor’s degree in Computer Science with a minor in Mathematics and Statistics from the University of Maryland. Niithiyn works closely with the Generative AI GTM team to enable AWS customers on multiple fronts and accelerate their adoption of generative AI.

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AWS Machine Learning Blog

OCTOBER 22, 2024

She has a decade of experience in DevOps, infrastructure, and ML. Her areas of focus include MLOps/LLMOps, generative AI, and computer vision. Brock builds solutions for MLOps, LLMOps, and generative AI, with experience spanning infrastructure, DevOps, cloud services, SDKs, and UIs.

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AWS Machine Learning Blog

OCTOBER 18, 2023

AWS Lambda is an event-driven compute service that lets you run code for virtually any type of application or backend service without provisioning or managing servers. Amazon Rekognition offers pre-trained and customizable computer vision (CV) capabilities to extract information and insights from your images and videos.

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Marktechpost

JULY 5, 2024

These courses cover foundational topics such as machine learning algorithms, deep learning architectures, natural language processing (NLP), computer vision, reinforcement learning, and AI ethics. Udacity offers comprehensive courses on AI designed to equip learners with essential skills in artificial intelligence.

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AWS Machine Learning Blog

MARCH 5, 2025

He has touched on most aspects of these projects, from infrastructure and DevOps to software development and AI/ML. After earning his bachelors degree in software engineering and a masters in computer vision and machine learning from Polytechnique Montreal, Philippe joined AWS to put his expertise to work for customers.

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AWS Machine Learning Blog

NOVEMBER 14, 2023

James’s work covers a wide range of ML use cases, with a primary interest in computer vision, deep learning, and scaling ML across the enterprise. He previously worked in the semiconductor industry developing large computer vision (CV) and natural language processing (NLP) models to improve semiconductor processes.

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AWS Machine Learning Blog

DECEMBER 5, 2023

Enterprises need a responsible and safer way to send sensitive information to the models without needing to take on the often prohibitively high overheads of on-premises DevOps. These concerns of privacy and data protection can slow down or limit the usage of LLMs in organizations.

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AWS Machine Learning Blog

OCTOBER 8, 2024

The face match is detected using Amazon Rekognition , which offers pre-trained and customizable computer vision (CV) capabilities to extract information and insights from your images and videos. This tool checks if the uploaded selfie matches the face on the ID by calling an endpoint deployed in API Gateway.

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Heartbeat

OCTOBER 5, 2023

MLOps, often seen as a subset of DevOps (Development Operations), focuses on streamlining the development and deployment of machine learning models. Where is LLMOps in DevOps and MLOps In MLOps, engineers are dedicated to enhancing the efficiency and impact of ML model deployment.

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Large Language Models DevOps Machine Learning Prompt Engineer 52

AWS Machine Learning Blog

FEBRUARY 2, 2024

Abdullahi holds a MSC in Computer Networking from Wichita State University and is a published author that has held roles across various technology domains such as DevOps, infrastructure modernization and AI. He holds an MSEE from the University of Michigan, where he worked on computer vision for autonomous vehicles.

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ODSC - Open Data Science

JULY 19, 2023

The repository also features architecture specifically designed for Computer Vision (CV) and Natural Language Processing (NLP) use cases. Security: We have included steps and best practices from GitHub’s advanced security scanning and credential scanning (also available in Azure DevOps) that can be incorporated into the workflow.

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AWS Machine Learning Blog

APRIL 19, 2023

It has intuitive helpers and utilities for modalities like computer vision, natural language processing, audio, time series, and tabular data. About the authors Fred Wu is a Senior Data Engineer at Sportradar, where he leads infrastructure, DevOps, and data engineering efforts for various NBA and NFL products.

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Marktechpost

JULY 17, 2023

The advantages of using synthetic data include easing restrictions when using private or controlled data, adjusting the data requirements to specific circumstances that cannot be met with accurate data, and producing datasets for DevOps teams to use for software testing and quality assurance.

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Mlearning.ai

MAY 11, 2023

Computer vision (OCR), 4. In the previous blog post I outlined how to use Computer vision (OCR) using the Python SDK and bash CLI. Photo by Practicing Datsy Azure Cognitive Services has 8 main tools: 1. Anomaly detection, 2. Chatbot/LLM (OpenAI), 3. Form Recognizer, 6. Metrics Advisor, 7. Speech Recognition, 8.

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Bugra Akyildiz

NOVEMBER 20, 2022

AI for DevOps to infuse AI/ML into the entire software development lifecycle to achieve high productivity. Libraries Collecting, labeling, and cleaning data for computer vision is a pain. AI for Customers to leverage AI/ML to create unparalleled user experiences and achieve exceptional user satisfaction using cloud services.

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The MLOps Blog

MARCH 28, 2023

The DevOps and Automation Ops departments are under the infrastructure team. On the computer vision team, we try to use the most straightforward solutions possible. The infrastructure team focuses on technology and delivers tools that other teams will adapt and use to work on their main deliverables.

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The MLOps Blog

JUNE 27, 2023

MLOps workflows for computer vision and ML teams Use-case-centric annotations. MLOps tools and platforms FAQ What devops tools are used in machine learning in 20233? The key features of Encord Annotate include: Support for all annotation types. Easy collaboration, annotator management, and QA workflows.

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Heartbeat

FEBRUARY 29, 2024

Furthermore, the software development process has evolved to embrace Agile methodologies, DevOps practices, and continuous integration/continuous delivery (CI/CD) pipelines. Written in older languages, legacy codebases can be particularly challenging to work with and update.

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The MLOps Blog

OCTOBER 3, 2023

For me, it was a little bit of a longer journey because I kind of had data engineering and cloud engineering and DevOps engineering in between. You see them all the time with a headline like: “data science, machine learning, Java, Python, SQL, or blockchain, computer vision.” It’s two things. They’re terrible people.

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ML Data Scientist Machine Learning Data Science 52

AWS Machine Learning Blog

AUGUST 15, 2023

The image moderation subsystem, as illustrated in the following diagram, utilized multiple self-hosted and self-trained computer vision models to detect images that violate Amazon guidelines. Combined with the DevOps efficiency gains, the Amazon Shopping team achieved significant cost savings.

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AWS Machine Learning Blog

JUNE 29, 2023

She has a decade of experience in DevOps, infrastructure, and ML. She is also the author of a book on computer vision. In his free time, Sean is an active open-source contributor and maintainer, and is the special interest group lead for TensorFlow Addons. Lauren Mullennex is a Senior AI/ML Specialist Solutions Architect at AWS.

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The MLOps Blog

MARCH 21, 2023

” — Isaac Vidas , Shopify’s ML Platform Lead, at Ray Summit 2022 Monitoring Monitoring is an essential DevOps practice, and MLOps should be no different. Collaboration The principles you have learned in this guide are mostly born out of DevOps principles. My Story DevOps Engineers Who they are?

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AWS Machine Learning Blog

AUGUST 29, 2024

He specializes in machine learning, AI, and computer vision domains, and holds a master’s degree in computer science from UT Dallas. He focuses on helping customers build, deploy, and migrate ML production workloads to SageMaker at scale. In his free time, he enjoys traveling and photography.

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AWS Machine Learning Blog

DECEMBER 18, 2024

With a strong foundation in computer vision and natural language processing, he is currently exploring the world of Generative AI and leveraging its powerful tools to craft innovative solutions for emerging challenges. He has expertise in AWS cloud services, DevOps practices, security, data analytics and generative AI.

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AWS Machine Learning Blog

JANUARY 9, 2025

His expertise includes designing scalable systems, implementing DevOps best practices, and optimizing cloud infrastructure for enterprise applications. He has extensive experience in deep learning, neural network optimization, computer vision, and cyber security.

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