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

FEBRUARY 11, 2025

Get started with SageMaker JumpStart SageMaker JumpStart is a machine learning (ML) hub that can help accelerate your ML journey. He focuses on helping customers build, deploy, and migrate ML production workloads to SageMaker at scale. Visit SageMaker JumpStart in SageMaker Studio now to get started.

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ML Machine Learning Python Computer Vision 79

Marktechpost

MAY 30, 2024

This article lists the top AI courses by Google that provide comprehensive training on various AI and machine learning technologies, equipping learners with the skills needed to excel in the rapidly evolving field of AI. Participants learn how to improve model accuracy and write scalable, specialized ML models.

Artificial Intelligence 130

Artificial Intelligence Artificial Intelligence BERT Computer Vision 130

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. She has worked in several product roles in Amazon for over 5 years.

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ML Python Data Scientist Natural Language Processing 82

AWS Machine Learning Blog

SEPTEMBER 29, 2023

In this post, we illustrate how to use a segmentation machine learning (ML) model to identify crop and non-crop regions in an image. Identifying crop regions is a core step towards gaining agricultural insights, and the combination of rich geospatial data and ML can lead to insights that drive decisions and actions.

Machine Learning 130

Machine Learning Data Scientist ML Python 130

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. Data Scientist at AWS, bringing a breadth of data science, ML engineering, MLOps, and AI/ML architecting to help businesses create scalable solutions on AWS.

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ML Metadata Data Scientist Machine Learning 99

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.

Computer Vision 81

Computer Vision ML Python Automation 81

Pickl AI

APRIL 19, 2023

Machine Learning is the part of Artificial Intelligence and computer science that emphasizes on the use of data and algorithms, imitating the way humans learn and improving accuracy. Machine Learning is becoming increasingly popular and crucial in today’s market for effective productivity and decision-making processes.

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Machine Learning ML Engineer Data Scientist ML 52

AWS Machine Learning Blog

APRIL 7, 2025

You can use state-of-the-art model architecturessuch as language models, computer vision models, and morewithout having to build them from scratch. This approach allows for greater flexibility and integration with existing AI and machine learning (AI/ML) workflows and pipelines. Choose Delete again to confirm.

Machine Learning 80

Machine Learning Large Language Models Python Automation 80

AWS Machine Learning Blog

APRIL 25, 2023

In this release, you can run your local machine learning (ML) Python code as a single-node Amazon SageMaker training job or multiple parallel jobs. This allows ML engineers and admins to configure these environment variables so data scientists can focus on ML model building and iterate faster.

Machine Learning 91

Machine Learning Data Scientist Python ML 91

Heartbeat

JULY 17, 2023

[link] Transfer learning using pre-trained computer vision models has become essential in modern computer vision applications. In this article, we will explore the process of fine-tuning computer vision models using PyTorch and monitoring the results using Comet.

Computer Vision 52

Computer Vision Auto-classification Deep Learning Machine Learning 52

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

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

DECEMBER 10, 2024

Today, we are excited to announce that Pixtral 12B ( pixtral-12b-2409 ), a state-of-the-art vision language model (VLM) from Mistral AI that excels in both text-only and multimodal tasks, is available for customers through Amazon SageMaker JumpStart. With SageMaker JumpStart, you can deploy models in a secure environment.

ML 96

ML Generative AI Computer Vision ML Engineer 96

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. He finds particular satisfaction in collaborating with customers to turn their ambitious technological visions into reality.

Auto-classification 81

Auto-classification Metadata Generative AI Machine Learning 81

AWS Machine Learning Blog

FEBRUARY 12, 2025

About the authors Daniel Zagyva is a Senior ML Engineer at AWS Professional Services. He specializes in developing scalable, production-grade machine learning solutions for AWS customers. His experience extends across different areas, including natural language processing, generative AI and machine learning operations.

LLM 76

LLM ML Natural Language Processing Machine Learning 76

AWS Machine Learning Blog

DECEMBER 1, 2023

Launched in 2019, Amazon SageMaker Studio provides one place for all end-to-end machine learning (ML) workflows, from data preparation, building and experimentation, training, hosting, and monitoring. About the Authors Mair Hasco is an AI/ML Specialist for Amazon SageMaker Studio. Get started on SageMaker Studio here.

Machine Learning 116

Machine Learning ML DevOps Data Science 116

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. Then, it tries to make predictions on the rest of the unlabeled data based on what it has learned.

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Generative AI ML Engineer Computer Vision Robotics 132

Pickl AI

JANUARY 23, 2023

Introduction to Machine Learning Frameworks In the present world, almost every organization is making use of machine learning and artificial intelligence in order to stay ahead of the competition. So, let us see the most popular and best machine learning frameworks and their uses.

Machine Learning 52

Machine Learning ML Neural Network Auto-classification 52

AWS Machine Learning Blog

NOVEMBER 30, 2023

Code Editor is based on Code-OSS , Visual Studio Code Open Source, and provides access to the familiar environment and tools of the popular IDE that machine learning (ML) developers know and love, fully integrated with the broader SageMaker Studio feature set. Sofian Hamiti is an AI/ML specialist Solutions Architect at AWS.

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Machine Learning ML LLM Python 121

AWS Machine Learning Blog

JUNE 27, 2023

When machine learning (ML) models are deployed into production and employed to drive business decisions, the challenge often lies in the operation and management of multiple models. That is where Provectus , an AWS Premier Consulting Partner with competencies in Machine Learning, Data & Analytics, and DevOps, stepped in.

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DevOps ML Machine Learning ML Engineer 112

The MLOps Blog

JUNE 27, 2023

How to evaluate MLOps tools and platforms Like every software solution, evaluating MLOps (Machine Learning Operations) tools and platforms can be a complex task as it requires consideration of varying factors. Pay-as-you-go pricing makes it easy to scale when needed.

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Machine Learning Metadata Data Scientist Data Quality 134

AWS Machine Learning Blog

MARCH 22, 2023

Generating this data can take months to gather and require large teams of labelers to prepare it for use in machine learning (ML). The workflow allows application developers and ML engineers to automate the custom label classification steps for any computer vision use case.

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Automation Machine Learning ML Computer Vision 91

The MLOps Blog

NOVEMBER 14, 2023

Deep learning models are typically highly complex. While many traditional machine learning models make do with just a couple of hundreds of parameters, deep learning models have millions or billions of parameters. After all, aren’t deep learning models closely related to their predecessors?

Deep Learning 111

Deep Learning Neural Network Convolutional Neural Networks Data Scientist 111

AWS Machine Learning Blog

SEPTEMBER 23, 2024

Machine learning (ML) projects are inherently complex, involving multiple intricate steps—from data collection and preprocessing to model building, deployment, and maintenance. About the Authors James Wu is a Senior AI/ML Specialist Solution Architect at AWS. helping customers design and build AI/ML solutions.

ML 80

ML Computer Vision Data Scientist Machine Learning 80

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 99

Data Scientist Generative AI Machine Learning ML 99

Flipboard

MARCH 13, 2023

This post is co-written with Mahima Agarwal, Machine Learning Engineer, and Deepak Mettem, Senior Engineering Manager, at VMware Carbon Black VMware Carbon Black is a renowned security solution offering protection against the full spectrum of modern cyberattacks. Vamshi Krishna Enabothala is a Sr.

Data Scientist 123

Data Scientist Auto-complete Machine Learning ML 123

AWS Machine Learning Blog

JANUARY 13, 2023

To mitigate these challenges, we propose using an open-source federated learning (FL) framework called FedML , which enables you to analyze sensitive HCLS data by training a global machine learning model from distributed data held locally at different sites. Reference. [1] 1] Kaissis, G.A., Makowski, M.R., Rückert, D.

Machine Learning 87

Machine Learning ML Algorithm Data Scientist 87

AWS Machine Learning Blog

OCTOBER 2, 2023

A successful deployment of a machine learning (ML) model in a production environment heavily relies on an end-to-end ML pipeline. Although developing such a pipeline can be challenging, it becomes even more complex when dealing with an edge ML use case.

DevOps 111

DevOps Automation ML Computer Vision 111

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. The more detailed AI ToolSuite requirements were driven by three example use cases: Develop a computer vision application aimed at object detection at the edge.

Data Scientist 108

Data Scientist ML Data Science Machine Learning 108

Towards AI

FEBRUARY 20, 2025

But who exactly is an LLM developer, and how are they different from software developers and ML engineers? Machine learning engineers specialize in training models from scratch and deploying them at scale. If you are starting out and prefer learning in a group, reach out in the thread! Meme of the week!

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Neural Network Explainability LLM Software Development 79

AWS Machine Learning Blog

MARCH 13, 2024

The audio moderation workflow uses Amazon Transcribe Toxicity Detection, which is a machine learning (ML)-powered capability that uses audio and text-based cues to identify and classify voice-based toxic content across seven categories, including sexual harassment, hate speech, threats, abuse, profanity, insults, and graphic language.

Natural Language Processing 127

Natural Language Processing LLM Prompt Engineer Prompt Engineering 127

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. He conducted research on machine learning and deep learning, specifically on topics like hyperparameter optimization and domain adaptation, presenting algorithms and papers.

Deep Learning 110

Deep Learning Machine Learning ML Data Scientist 110

AWS Machine Learning Blog

OCTOBER 2, 2024

This is often referred to as platform engineering and can be neatly summarized by the mantra “You (the developer) build and test, and we (the platform engineering team) do all the rest!” Leveraging her expertise in Computer Vision and Deep Learning, she empowers customers to harness the power of the ML in AWS cloud efficiently.

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Generative AI Data Ingestion AI AI 115

Chatbots Life

MAY 16, 2023

10Clouds is a software consultancy, development, ML, and design house based in Warsaw, Poland. Services : Mobile app development, web development, blockchain technology implementation, 360′ design services, DevOps, OpenAI integrations, machine learning, and MLOps. Elite Service Delivery partner of NVIDIA.

Generative AI 92

Generative AI Chatbots Conversational AI Software Development 92

AWS Machine Learning Blog

JANUARY 25, 2023

Model explainability refers to the process of relating the prediction of a machine learning (ML) model to the input feature values of an instance in humanly understandable terms. For more information, refer to What Is Fairness and Model Explainability for Machine Learning Predictions.

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Explainability Algorithm Natural Language Processing Machine Learning 81

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 88