Hacker News

JANUARY 27, 2024

Computer science teachers, software experts share their advice on ML assistants

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AWS Machine Learning Blog

OCTOBER 16, 2024

Amazon SageMaker supports geospatial machine learning (ML) capabilities, allowing data scientists and ML engineers to build, train, and deploy ML models using geospatial data. SageMaker Processing provisions cluster resources for you to run city-, country-, or continent-scale geospatial ML workloads.

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Flipboard

MAY 15, 2025

Qualtrics harnesses the power of generative AI, cutting-edge machine learning (ML), and the latest in natural language processing (NLP) to provide new purpose-built capabilities that are precision-engineered for experience management (XM). It uses managed AWS services like SageMaker and Amazon Bedrock to enable the entire ML lifecycle.

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Hacker News

NOVEMBER 19, 2024

Here are a few of the things that you might do as an AI Engineer at TigerEye: - Design, develop, and validate statistical models to explain past behavior and to predict future behavior of our customers’ sales teams - Own training, integration, deployment, versioning, and monitoring of ML components - Improve TigerEye’s existing metrics collection and (..)

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Flipboard

SEPTEMBER 16, 2023

Machine Learning (ML), a subfield of Artificial Intelligence (AI), … These third-party libraries are an essential part of any AI developer’s toolkit.

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MARCH 31, 2025

Observability and monitoring is the most cited challenge when moving ML models into production. The Institute for Ethical AI & Machine Learning

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NOVEMBER 26, 2023

Amazon Redshift ML empowers data analysts and database developers to integrate the capabilities of machine learning and artificial intelligence into …

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Flipboard

DECEMBER 2, 2024

To learn more about the ModelBuilder class, refer to Package and deploy classical ML and LLMs easily with Amazon SageMaker, part 1: PySDK Improvements. Lokeshwaran Ravi is a Senior Deep Learning Compiler Engineer at AWS, specializing in ML optimization, model acceleration, and AI security. In this example, you deploy the Meta Llama 3.1

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AWS Machine Learning Blog

NOVEMBER 29, 2023

Data preparation is a crucial step in any machine learning (ML) workflow, yet it often involves tedious and time-consuming tasks. With this integration, SageMaker Canvas provides customers with an end-to-end no-code workspace to prepare data, build and use ML and foundations models to accelerate time from data to business insights.

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APRIL 24, 2025

About the authors Renuka Kumar is a Senior Engineering Technical Lead at Cisco, where she has architected and led the development of Ciscos Cloud Security BUs AI/ML capabilities in the last 2 years, including launching first-to-market innovations in this space. She holds an undergraduate degree in Computer Science & Engineering.

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Flipboard

JANUARY 24, 2025

Overview of vector search and the OpenSearch Vector Engine Vector search is a technique that improves search quality by enabling similarity matching on content that has been encoded by machine learning (ML) models into vectors (numerical encodings). These benchmarks arent designed for evaluating ML models.

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Flipboard

NOVEMBER 30, 2023

Amazon SageMaker is a fully managed service that enables developers and data scientists to quickly and effortlessly build, train, and deploy machine learning (ML) models at any scale. Deploy traditional models to SageMaker endpoints In the following examples, we showcase how to use ModelBuilder to deploy traditional ML models.

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AWS Machine Learning Blog

MARCH 8, 2023

Amazon SageMaker is a fully managed machine learning (ML) service. With SageMaker, data scientists and developers can quickly and easily build and train ML models, and then directly deploy them into a production-ready hosted environment. Create a custom container image for ML model training and push it to Amazon ECR.

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Flipboard

MAY 30, 2025

The quality assurance process includes automated testing methods combining ML-, algorithm-, or LLM-based evaluations. In addition, the process employs traditional ML procedures such as named entity recognition (NER) or estimation of final confidence with regression models. The team extensively used fine-tuned SLMs.

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Flipboard

DECEMBER 2, 2024

This long-awaited capability is a game changer for our customers using the power of AI and machine learning (ML) inference in the cloud. The scale down to zero feature presents new opportunities for how businesses can approach their cloud-based ML operations. However, it’s possible to forget to delete these endpoints when you’re done.

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Flipboard

OCTOBER 2, 2023

The more physicists use artificial intelligence and machine learning, the more important it becomes for them to understand why the technology works …

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AUGUST 17, 2023

Many practitioners are extending these Redshift datasets at scale for machine learning (ML) using Amazon SageMaker , a fully managed ML service, with requirements to develop features offline in a code way or low-code/no-code way, store featured data from Amazon Redshift, and make this happen at scale in a production environment.

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Analytics Vidhya

JUNE 12, 2023

Introduction Meet Tajinder, a seasoned Senior Data Scientist and ML Engineer who has excelled in the rapidly evolving field of data science. Tajinder’s passion for unraveling hidden patterns in complex datasets has driven impactful outcomes, transforming raw data into actionable intelligence.

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PyImageSearch

DECEMBER 30, 2024

Hugging Face Spaces is a platform for deploying and sharing machine learning (ML) applications with the community. It offers an interactive interface, enabling users to explore ML models directly in their browser without the need for local setup. Or requires a degree in computer science? Thats not the case.

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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 holds a Bachelors degree in Computer Science and Bioinformatics. Marc Karp is an ML Architect with the Amazon SageMaker Service team.

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AWS Machine Learning Blog

NOVEMBER 18, 2024

It makes it simple for you to build modern machine learning (ML) augmented search experiences, generative AI applications, and analytics workloads without having to manage the underlying infrastructure. He is focused on OpenSearch Serverless and has years of experience in networking, security and AI/ML.

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AWS Machine Learning Blog

NOVEMBER 30, 2023

Amazon SageMaker is a fully managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning (ML) models at scale. For more information, refer to Package and deploy classical ML and LLMs easily with Amazon SageMaker, part 1: PySDK Improvements.

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AWS Machine Learning Blog

APRIL 8, 2025

With the support of AWS, iFood has developed a robust machine learning (ML) inference infrastructure, using services such as Amazon SageMaker to efficiently create and deploy ML models. In this post, we show how iFood uses SageMaker to revolutionize its ML operations.

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AWS Machine Learning Blog

OCTOBER 29, 2024

This engine uses artificial intelligence (AI) and machine learning (ML) services and generative AI on AWS to extract transcripts, produce a summary, and provide a sentiment for the call. This post provides guidance on how you can create a video insights and summarization engine using AWS AI/ML services.

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AWS Machine Learning Blog

JUNE 25, 2024

This solution simplifies the integration of advanced monitoring tools such as Prometheus and Grafana, enabling you to set up and manage your machine learning (ML) workflows with AWS AI Chips. By deploying the Neuron Monitor DaemonSet across EKS nodes, developers can collect and analyze performance metrics from ML workload pods.

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Flipboard

SEPTEMBER 25, 2023

Being a compiled language, C++ can translate into machine code before execution, making it ideal for computationally intensive jobs like training …

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AWS Machine Learning Blog

NOVEMBER 13, 2024

With an academic background in computer science and engineering, he started developing his AI/ML passion at university; as a member of the natural language processing and generative AI community within AWS, Luca helps customers be successful while adopting AI/ML services.

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AWS Machine Learning Blog

OCTOBER 10, 2024

in Computer Science from New York University. She has extensive hands-on experience in solving customers’ business use cases by utilizing generative AI as well as traditional AI/ML solutions. degree in Data Science from New York University. degree in Computer Science from UC Davis. He holds Ph.D.

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Flipboard

MAY 16, 2023

In my last project, I had to come up with some code and algorithm to solve an interesting problem. I realized that it could lead to some …

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Flipboard

JUNE 4, 2025

For more information on how SageMaker HyperPods resiliency helps save costs while training, check out Reduce ML training costs with Amazon SageMaker HyperPod. Before joining AWS, Aman graduated from Rice University with degrees in computer science, mathematics, and entrepreneurship.

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AWS Machine Learning Blog

JANUARY 31, 2025

Increasingly, FMs are completing tasks that were previously solved by supervised learning, which is a subset of machine learning (ML) that involves training algorithms using a labeled dataset. His passion is for solving challenging real-world computer vision problems and exploring new state-of-the-art methods to do so.

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AWS Machine Learning Blog

FEBRUARY 11, 2025

GraphStorm is a low-code enterprise graph machine learning (ML) framework that provides ML practitioners a simple way of building, training, and deploying graph ML solutions on industry-scale graph data. We encourage ML practitioners working with large graph data to try GraphStorm.

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Flipboard

SEPTEMBER 7, 2023

Brands are under immense pressure to advance and evolve as customer buying trends change, budgets shrink, and broad economic factors become increasingly complicated. In response, many companies are turning to emerging applications of well-known technologies like artificial intelligence (AI) and …

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Flipboard

SEPTEMBER 4, 2023

In a review published in Engineering, scientists explore the burgeoning field of machine learning (ML) and its applications in chemistry.

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AWS Machine Learning Blog

NOVEMBER 14, 2023

Examples include: Cultivating distrust in the media Undermining the democratic process Spreading false or discredited science (for example, the anti-vax movement) Advances in artificial intelligence (AI) and machine learning (ML) have made developing tools for creating and sharing fake news even easier. in computer science. -

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Dataconomy

DECEMBER 18, 2024

Artificial Intelligence (AI) is a field of computer science focused on creating systems that perform tasks requiring human intelligence, such as language processing, data analysis, decision-making, and learning. Since DL falls under ML, this discussion will primarily focus on machine learning.

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Flipboard

FEBRUARY 21, 2025

With the rise of AI/ML, OpenSearch added the ability to compute a similarity score for the distance between vectors. To search with vectors, you add vector embeddings produced by FMs and other AI/ML technologies to your documents.

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