Flipboard

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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ML ML Machine Learning Machine Learning 142

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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ML ML Clustering Machine Learning 118

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 (..)

Computer Science 162

Computer Science Computer Science ML ML 162

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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ML ML Artificial Intelligence Artificial Intelligence 151

Flipboard

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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SQL Database AWS ML 142

Flipboard

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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ML ML Data Analyst Artificial Intelligence 152

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 ML ML Machine Learning 142

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.

Data Preparation 125

Data Preparation ML ML Data Quality 125

NYU Center for Data Science

SEPTEMBER 28, 2023

Building on this momentum is a dynamic research group at the heart of CDS called the Machine Learning and Language (ML²) group. By 2020, ML² was a thriving community, primarily known for its recurring speaker series where researchers presented their work to peers. What does it mean to work in NLP in the age of LLMs?

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Machine Learning Machine Learning ML ML 98

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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K-nearest Neighbors ML ML Algorithm 143

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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ML ML AWS Python 166

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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ML ML AWS Python 132

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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ML ML AWS Machine Learning 148

ODSC - Open Data Science

APRIL 28, 2023

Be sure to check out her talk, “ Power trusted AI/ML Outcomes with Data Integrity ,” there! Due to the tsunami of data available to organizations today, artificial intelligence (AI) and machine learning (ML) are increasingly important to businesses seeking competitive advantage through digital transformation.

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ML ML Data Silos Data Quality 98

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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ML ML Artificial Intelligence Artificial Intelligence 172

Flipboard

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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ML ML AWS Data Warehouse 123

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.

Data Scientist 306

Data Scientist Machine Learning Machine Learning Data Science 306

AWS Machine Learning Blog

JUNE 9, 2023

a low-code enterprise graph machine learning (ML) framework to build, train, and deploy graph ML solutions on complex enterprise-scale graphs in days instead of months. With GraphStorm, we release the tools that Amazon uses internally to bring large-scale graph ML solutions to production. license on GitHub. GraphStorm 0.1

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ML ML K-nearest Neighbors Machine Learning 104

AWS Machine Learning Blog

MAY 10, 2023

Project Jupyter is a multi-stakeholder, open-source project that builds applications, open standards, and tools for data science, machine learning (ML), and computational science. Given the importance of Jupyter to data scientists and ML developers, AWS is an active sponsor and contributor to Project Jupyter.

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ML ML AWS AI 104

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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ML ML AWS Python 128

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 …

ML 162

ML ML Computer Science Computer Science 162

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 AI AI ML 111

Dataconomy

MAY 2, 2023

What do machine learning engineers do: ML engineers design and develop machine learning models The responsibilities of a machine learning engineer entail developing, training, and maintaining machine learning systems, as well as performing statistical analyses to refine test results. Is ML engineering a stressful job?

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ML ML Machine Learning Machine Learning 110

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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AWS ML ML Clustering 96

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 AI AI Natural Language Processing 132

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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ML ML Algorithm AI 148

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.

Supervised Learning 100

Supervised Learning AWS Data Scientist ML 100

NYU Center for Data Science

AUGUST 29, 2024

Puli recently finished his PhD in Computer Science at NYU’s Courant Institute, advised by CDS Assistant Professor of Computer Science and Data Science Rajesh Ranganath. He is partly supported by the Apple Scholars in AI/ML PhD fellowship. Puli earned his MS in Computer Science from NYU in 2017.

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Hypothesis Testing Computer Science Computer Science Data Science 75

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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AI AI Machine Learning Machine Learning 91

NYU Center for Data Science

JUNE 8, 2023

The free week-long course was launched and generously funded by the NYU ML² Machine Learning for Language Lab and organized by students from the CDS and NYU’s Courant Institute. It includes hands-on labs and lectures taught by renowned researchers in the fields of artificial intelligence and machine learning.

Machine Learning 119

Machine Learning Machine Learning Natural Language Processing Artificial Intelligence 119

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 …

ML 143

ML ML Artificial Intelligence Artificial Intelligence 143

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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Machine Learning Machine Learning ML ML 163

Dataconomy

APRIL 3, 2025

in Computer Science and Engineering with a stellar GPA of 8.61, Harshit set a high bar for aspiring innovators. He re-architected big-data systems behind ML recommendation pipelines for using serverless architectures, ensuring privacy compliance for all datasets. During competitions, Harshit developed technology skills.

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Big Data Big Data Machine Learning Machine Learning 91

ODSC - Open Data Science

APRIL 14, 2025

Finale Doshi Velez, PhD, Professor at Harvard University Finale Doshi-Velez is a Herchel Smith Professor in Computer Science at the Harvard Paulson School of Engineering and Applied Sciences. He has taught Python and ML since 2015 through LinkedIn Learning, Stanford, andUCSD.

Data Science 52

Data Science Machine Learning Machine Learning ML 52

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. -

Computer Science 131

Computer Science Computer Science AWS Python 131

Dataconomy

APRIL 4, 2025

Understanding of AI, ML, and NLP A strong grasp of machine learning concepts, algorithms, and natural language processing is essential in this role. For instance, showing the desired tone or format can streamline the generation process. This core knowledge helps in optimizing AI performance and the effectiveness of prompts.

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AI AI Natural Language Processing Machine Learning 91

AWS Machine Learning Blog

MARCH 3, 2025

This design simplifies the complexity of distributed training while maintaining the flexibility needed for diverse machine learning (ML) workloads, making it an ideal solution for enterprise AI development. The AWS AI/ML community offers extensive resources, including workshops and technical guidance, to support your implementation journey.

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Clustering AWS ML ML 99