AWS Machine Learning Blog

DECEMBER 12, 2024

The new SDK is designed with a tiered user experience in mind, where the new lower-level SDK ( SageMaker Core ) provides access to full breadth of SageMaker features and configurations, allowing for greater flexibility and control for ML engineers.

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ML Python Data Scientist Natural Language Processing 99

Viso.ai

FEBRUARY 11, 2024

About us: We are viso.ai, the creators of the end-to-end computer vision platform, Viso Suite. With Viso Suite, enterprises can get started using computer vision to solve business challenges without any code. Viso Suite : the only end-to-end computer vision platform Detectron2: What’s Inside?

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Computer Vision Robotics Deep Learning Large Language Models 52

Marktechpost

MAY 30, 2024

Introduction to AI and Machine Learning on Google Cloud This course introduces Google Cloud’s AI and ML offerings for predictive and generative projects, covering technologies, products, and tools across the data-to-AI lifecycle. Participants learn how to improve model accuracy and write scalable, specialized ML models.

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Artificial Intelligence Artificial Intelligence BERT Computer Vision 131

Flipboard

FEBRUARY 28, 2023

in Electrical Engineering and a B.S. More posts by this contributor 4 questions to ask before building a computer vision model During the past six months, we have witnessed some incredible developments in AI. He holds an S.M. in Applied Physics from Harvard University, an M.S. in Physics from Stanford University.

Generative AI 132

Generative AI ML Engineer Computer Vision Robotics 132

Flipboard

OCTOBER 9, 2023

Getting Used to Docker for Machine Learning Introduction Docker is a powerful addition to any development environment, and this especially rings true for ML Engineers or enthusiasts who want to get started with experimentation without having to go through the hassle of setting up several drivers, packages, and more.

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Machine Learning Computer Vision Deep Learning Python 153

AWS Machine Learning Blog

FEBRUARY 11, 2025

is a state-of-the-art vision segmentation model designed for high-performance computer vision tasks, enabling advanced object detection and segmentation workflows. You can now use state-of-the-art model architectures, such as language models, computer vision models, and more, without having to build them from scratch.

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Computer Vision ML Python Automation 81

AWS Machine Learning Blog

OCTOBER 28, 2024

Real-world applications vary in inference requirements for their artificial intelligence and machine learning (AI/ML) solutions to optimize performance and reduce costs. You can use this framework as a starting point to monitor your custom metrics or handle other unique requirements for model quality monitoring in your AI/ML applications.

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ML Metadata Data Scientist DevOps 114

Towards AI

JANUARY 6, 2025

Artificial Intelligence graduate certificate by STANFORD SCHOOL OF ENGINEERING Artificial Intelligence graduate certificate; taught by Andrew Ng, and other eminent AI prodigies; is a popular course that dives deep into the principles and methodologies of AI and related fields.

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Artificial Intelligence Artificial Intelligence Computer Vision Deep Learning 105

AWS Machine Learning Blog

DECEMBER 10, 2024

You can now use state-of-the-art model architectures, such as language models, computer vision models, and more, without having to build them from scratch. These pre-trained models serve as powerful starting points that can be deeply customized to address specific use cases.

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ML Generative AI Computer Vision ML Engineer 103

Flipboard

JUNE 20, 2023

Machine learning (ML) engineers have traditionally focused on striking a balance between model training and deployment cost vs. performance. This is important because training ML models and then using the trained models to make predictions (inference) can be highly energy-intensive tasks.

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Machine Learning BERT Deep Learning ML Engineer 123

AWS Machine Learning Blog

DECEMBER 1, 2023

This updated user experience (UX) provides data scientists, data engineers, and ML engineers more choice on where to build and train their ML models within SageMaker Studio. Lauren Mullennex is a Senior AI/ML Specialist Solutions Architect at AWS. She has a decade of experience in DevOps, infrastructure, and ML.

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Machine Learning ML DevOps Data Science 123

AWS Machine Learning Blog

FEBRUARY 12, 2025

Machine learning (ML) engineers must make trade-offs and prioritize the most important factors for their specific use case and business requirements. She leads machine learning projects in various domains such as computer vision, natural language processing, and generative AI.

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Auto-classification Metadata Generative AI Machine Learning 95

Towards AI

APRIL 27, 2023

Because selecting it judicially reduces the data movement, data processing computation, and data labeling costs downstream Then once the data is collected, synchronized, and selected, it needs to be labeled, which, again, no one from the AI team wants to do. SAM from Meta AI — the chatGPT moment for computer vision AI It’s a disruption.

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Automation Auto-complete Computer Vision ChatGPT 98

AWS Machine Learning Blog

SEPTEMBER 23, 2024

Throughout this exercise, you use Amazon Q Developer in SageMaker Studio for various stages of the development lifecycle and experience firsthand how this natural language assistant can help even the most experienced data scientists or ML engineers streamline the development process and accelerate time-to-value.

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ML Computer Vision Data Scientist Machine Learning 90

Allen AI

NOVEMBER 8, 2023

Patrick Beukema is the Lead ML Engineer for Skylight Patrick Beukema is the Lead ML Engineer for Skylight. Later this month, we will be adding a third real-time satellite computer vision service for vessel detection using the Sentinel-2 optical imagery from the European Space Agency.

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Computer Vision ML Engineer ML Neural Network 52

Towards AI

FEBRUARY 20, 2025

But who exactly is an LLM developer, and how are they different from software developers and ML engineers? If you are skilled in Python or computer vision, diffusion models, or GANS, you might be a great fit. Well, briefly, software developers focus on building traditional applications using explicit code.

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Neural Network Explainability LLM Software Development 79

The MLOps Blog

NOVEMBER 14, 2023

Visualizing deep learning models can help us with several different objectives: Interpretability and explainability: The performance of deep learning models is, at times, staggering, even for seasoned data scientists and ML engineers. Data scientists and ML engineers: Creating and training deep learning models is no easy feat.

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Deep Learning Neural Network Convolutional Neural Networks Data Scientist 111

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). We initiated a series of enhancements to deliver managed MLOps platform and augment ML engineering.

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DevOps ML Machine Learning ML Engineer 115

Pickl AI

APRIL 19, 2023

Different industries from education, healthcare to marketing, retail and ecommerce require Machine Learning Engineers. Job market will experience a rise of 13% by 2026 for ML Engineers Why is Machine Learning Important? Accordingly, an entry-level ML engineer will earn around 5.1 Consequently.

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Machine Learning ML Engineer Data Scientist ML 52

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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DevOps Automation ML Computer Vision 122

Chatbots Life

MAY 16, 2023

Services : AI Solution Development, ML Engineering, Data Science Consulting, NLP, AI Model Development, AI Strategic Consulting, Computer Vision. Data Monsters can help companies deploy, train and test machine learning pipelines for natural language processing and computer vision.

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Generative AI Chatbots Conversational AI Software Development 92

AWS Machine Learning Blog

MARCH 13, 2024

The traditional method of training an in-house classification model involves cumbersome processes such as data annotation, training, testing, and model deployment, requiring the expertise of data scientists and ML engineers. LLMs, in contrast, offer a high degree of flexibility.

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Natural Language Processing LLM Prompt Engineer Prompt Engineering 136

AWS Machine Learning Blog

MARCH 22, 2023

The workflow allows application developers and ML engineers to automate the custom label classification steps for any computer vision use case. Conclusion In this post, we walked through a Step Functions workflow to create a dataset and then train, evaluate, and use a Rekognition Custom Labels model.

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Automation Machine Learning Computer Vision ML 98

AWS Machine Learning Blog

OCTOBER 4, 2024

About the Authors Akarsha Sehwag is a Data Scientist and ML Engineer in AWS Professional Services with over 5 years of experience building ML based solutions. Leveraging her expertise in Computer Vision and Deep Learning, she empowers customers to harness the power of the ML in AWS cloud efficiently.

Data Scientist 101

Data Scientist Generative AI Machine Learning ML 101

TheSequence

MAY 21, 2023

📢 Event: apply(risk), the ML Engineering Community Conference for Building Risk & Fraud Detection Systems Want to connect with the ML engineering community and learn best practices from ML practitioners at Affirm, Remitly, Block, Tide, and more, on how to build risk and fraud detection systems?

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Generative AI ML Engineer ETL LLM 64

Viso.ai

FEBRUARY 27, 2024

Since its inception in 2015, the YOLO (You Only Look Once) object-detection algorithm has been closely followed by tech enthusiasts, data scientists, ML engineers, and more, gaining a massive following due to its open-source nature and community contributions. Viso Suite is the end-to-end platform for no code computer vision.

Neural Network 52

Neural Network Computer Vision Convolutional Neural Networks Python 52

AWS Machine Learning Blog

NOVEMBER 16, 2023

Amazon SageMaker provides purpose-built tools for machine learning operations (MLOps) to help automate and standardize processes across the ML lifecycle. In this post, we describe how Philips partnered with AWS to develop AI ToolSuite—a scalable, secure, and compliant ML platform on SageMaker.

Data Scientist 124

Data Scientist ML Data Science Automation 124

AWS Machine Learning Blog

MAY 5, 2023

Voxel51 is the company behind FiftyOne, the open-source toolkit for building high-quality datasets and computer vision models. Solution overview Ground Truth is a fully self-served and managed data labeling service that empowers data scientists, machine learning (ML) engineers, and researchers to build high-quality datasets.

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Metadata Computer Vision Machine Learning Data Scientist 100

AWS Machine Learning Blog

NOVEMBER 30, 2023

In this example, Code Editor can be used by an ML engineering team who needs advanced IDE features to debug their code and deploy the endpoint. He has worked on projects in different domains, including MLOps, computer vision, and NLP, involving a broad set of AWS services. You can find the sample code in this GitHub repo.

Machine Learning 126

Machine Learning ML LLM Software Engineer 126

AWS Machine Learning Blog

JANUARY 25, 2023

Amazon SageMaker Clarify is a feature of Amazon SageMaker that enables data scientists and ML engineers to explain the predictions of their ML models. He has worked with organizations ranging from large enterprises to mid-sized startups on problems related to distributed computing, and Artificial Intelligence.

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Explainability Algorithm Natural Language Processing Machine Learning 97

AWS Machine Learning Blog

FEBRUARY 12, 2025

About the authors Daniel Zagyva is a Senior ML Engineer at AWS Professional Services. Moran Beladev is a Senior ML Manager at Booking.com. Manos Stergiadis is a Senior ML Scientist at Booking.com. He specializes in developing scalable, production-grade machine learning solutions for AWS customers.

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LLM ML Natural Language Processing Machine Learning 77

Snorkel AI

MAY 4, 2023

Reinforcement learning has shown great promise in mastering complex games and decision-making tasks, while computer vision has progressed rapidly, allowing for more accurate image recognition, object detection, and scene understanding. Enterprise use cases: predictive AI, generative AI, NLP, computer vision, conversational AI.

Computer Vision 52

Computer Vision Large Language Models Natural Language Processing AI 52

Snorkel AI

MAY 4, 2023

Reinforcement learning has shown great promise in mastering complex games and decision-making tasks, while computer vision has progressed rapidly, allowing for more accurate image recognition, object detection, and scene understanding. Enterprise use cases: predictive AI, generative AI, NLP, computer vision, conversational AI.

Computer Vision 52

Computer Vision Large Language Models Natural Language Processing AI 52

AWS Machine Learning Blog

SEPTEMBER 25, 2024

You can now use state-of-the-art model architectures, such as language models, computer vision models, and more, without having to build them from scratch. These pre-trained models serve as powerful starting points that can be deeply customized to address specific use cases. Search for the embedding and text generation endpoints.

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Software Engineer Software Development ML Python 129

Flipboard

MARCH 13, 2023

After meticulous analysis of the evaluation results, the data scientist or ML engineer can deploy the new model if the performance of the newly trained model is better compared to the previous version. He is passionate about recommendation systems, NLP, and computer vision areas in AI and ML.

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Data Scientist Auto-complete Machine Learning ML 123

ODSC - Open Data Science

JULY 19, 2023

Machine Learning Operations (MLOps) can significantly accelerate how data scientists and ML engineers meet organizational needs. A well-implemented MLOps process not only expedites the transition from testing to production but also offers ownership, lineage, and historical data about ML artifacts used within the team.

Machine Learning 52

Machine Learning Data Drift Data Science Data Scientist 52

AWS Machine Learning Blog

NOVEMBER 20, 2023

KT’s AI Food Tag is an AI-based dietary management solution that identifies the type and nutritional content of food in photos using a computer vision model. 24xlarge instances.

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Deep Learning Machine Learning ML Data Scientist 121