Analytics Vidhya

JANUARY 11, 2023

Introduction With regard to educating its community about data science, Analytics Vidhya has long been at the forefront. We periodically hold “DataHour” events to increase community interest in studying data science. The post Introduction to BigQuery ML appeared first on Analytics Vidhya.

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AWS Machine Learning Blog

NOVEMBER 13, 2024

Recognizing this need, we have developed a Chrome extension that harnesses the power of AWS AI and generative AI services, including Amazon Bedrock , an AWS managed service to build and scale generative AI applications with foundation models (FMs). The user signs in by entering a user name and a password.

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AWS Machine Learning Blog

FEBRUARY 21, 2025

Rockets legacy data science environment challenges Rockets previous data science solution was built around Apache Spark and combined the use of a legacy version of the Hadoop environment and vendor-provided Data Science Experience development tools.

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AWS Machine Learning Blog

NOVEMBER 7, 2024

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. You can use AWS services such as Application Load Balancer to implement this approach. API Gateway also provides a WebSocket API. These components are illustrated in the following diagram.

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Flipboard

OCTOBER 25, 2023

After decades of digitizing everything in your enterprise, you may have an enormous amount of data, but with dormant value. However, with the help of AI and machine learning (ML), new software tools are now available to unearth the value of unstructured data. The solution integrates data in three tiers.

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AWS Machine Learning Blog

OCTOBER 22, 2024

Amazon SageMaker is a cloud-based machine learning (ML) platform within the AWS ecosystem that offers developers a seamless and convenient way to build, train, and deploy ML models. By using a combination of AWS services, you can implement this feature effectively, overcoming the current limitations within SageMaker.

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AWS Machine Learning Blog

JANUARY 5, 2024

This post was written in collaboration with Bhajandeep Singh and Ajay Vishwakarma from Wipro’s AWS AI/ML Practice. Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models.

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AWS Machine Learning Blog

NOVEMBER 26, 2024

Amazon SageMaker Studio is the first integrated development environment (IDE) purposefully designed to accelerate end-to-end machine learning (ML) development. You can create multiple Amazon SageMaker domains , which define environments with dedicated data storage, security policies, and networking configurations.

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AWS Machine Learning Blog

APRIL 3, 2025

At the heart of this transformation is the OMRON Data & Analytics Platform (ODAP), an innovative initiative designed to revolutionize how the company harnesses its data assets. The robust security features provided by Amazon S3, including encryption and durability, were used to provide data protection.

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Pickl AI

DECEMBER 26, 2024

Summary: “Data Science in a Cloud World” highlights how cloud computing transforms Data Science by providing scalable, cost-effective solutions for big data, Machine Learning, and real-time analytics. Advancements in data processing, storage, and analysis technologies power this transformation.

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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. Prior to joining AWS, Dr. Li held data science roles in the financial and retail industries. Li held data science roles in the financial and retail industries.

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Flipboard

DECEMBER 3, 2024

Syngenta and AWS collaborated to develop Cropwise AI , an innovative solution powered by Amazon Bedrock Agents , to accelerate their sales reps’ ability to place Syngenta seed products with growers across North America. The collaboration between Syngenta and AWS showcases the transformative power of LLMs and AI agents.

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AWS Machine Learning Blog

OCTOBER 24, 2024

Machine learning (ML) helps organizations to increase revenue, drive business growth, and reduce costs by optimizing core business functions such as supply and demand forecasting, customer churn prediction, credit risk scoring, pricing, predicting late shipments, and many others. Let’s learn about the services we will use to make this happen.

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How to Learn Machine Learning

DECEMBER 24, 2024

If you’re diving into the world of machine learning, AWS Machine Learning provides a robust and accessible platform to turn your data science dreams into reality. Whether you’re a solo developer or part of a large enterprise, AWS provides scalable solutions that grow with your needs. Hey dear reader!

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Flipboard

NOVEMBER 24, 2023

With that, the need for data scientists and machine learning (ML) engineers has grown significantly. Data scientists and ML engineers require capable tooling and sufficient compute for their work. Data scientists and ML engineers require capable tooling and sufficient compute for their work.

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AWS Machine Learning Blog

DECEMBER 16, 2024

Getting started with SageMaker JumpStart SageMaker JumpStart is a machine learning (ML) hub that can help accelerate your ML journey. These models are fully customizable for your use case with your data, and you can deploy them into production using either the UI or SDK.

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AWS Machine Learning Blog

OCTOBER 20, 2023

Customers of every size and industry are innovating on AWS by infusing machine learning (ML) into their products and services. Recent developments in generative AI models have further sped up the need of ML adoption across industries.

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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. SageMaker Model Monitor monitors the quality of SageMaker ML models in production. Your client applications invoke this endpoint to get inferences from the model.

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AWS Machine Learning Blog

APRIL 4, 2025

They use real-time data and machine learning (ML) to offer customized loans that fuel sustainable growth and solve the challenges of accessing capital. They fine-tuned this model using their proprietary dataset and in-house data science expertise. The pipeline leverages several AWS services familiar to Lumis team.

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Flipboard

DECEMBER 2, 2024

Today at AWS re:Invent 2024, we are excited to announce a new feature for Amazon SageMaker inference endpoints: the ability to scale SageMaker inference endpoints to zero instances. This long-awaited capability is a game changer for our customers using the power of AI and machine learning (ML) inference in the cloud.

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AWS Machine Learning Blog

NOVEMBER 14, 2024

We recently announced the general availability of cross-account sharing of Amazon SageMaker Model Registry using AWS Resource Access Manager (AWS RAM) , making it easier to securely share and discover machine learning (ML) models across your AWS accounts.

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AWS Machine Learning Blog

DECEMBER 2, 2024

Today, we are introducing three key advancements that further expand our AI inference capabilities: NVIDIA NIM microservices are now available in AWS Marketplace for SageMaker Inference deployments , providing customers with easy access to state-of-the-art generative AI models. or Mixtral.

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AWS Machine Learning Blog

JULY 8, 2024

As industries begin adopting processes dependent on machine learning (ML) technologies, it is critical to establish machine learning operations (MLOps) that scale to support growth and utilization of this technology. There were noticeable challenges when running ML workflows in the cloud.

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AWS Machine Learning Blog

OCTOBER 1, 2024

Over the last 18 months, AWS has announced more than twice as many machine learning (ML) and generative artificial intelligence (AI) features into general availability than the other major cloud providers combined. The following figure highlights where AWS lands in the DSML Magic Quadrant.

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Flipboard

MARCH 7, 2023

This post presents a solution that uses a workflow and AWS AI and machine learning (ML) services to provide actionable insights based on those transcripts. We use multiple AWS AI/ML services, such as Contact Lens for Amazon Connect and Amazon SageMaker , and utilize a combined architecture.

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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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Data Science Dojo

FEBRUARY 20, 2023

Machine learning (ML) is the technology that automates tasks and provides insights. It allows data scientists to build models that can automate specific tasks. It comes in many forms, with a range of tools and platforms designed to make working with ML more efficient. It is also useful for training models on smaller datasets.

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Pickl AI

DECEMBER 25, 2024

Summary: Business Analytics focuses on interpreting historical data for strategic decisions, while Data Science emphasizes predictive modeling and AI. Introduction In today’s data-driven world, businesses increasingly rely on analytics and insights to drive decisions and gain a competitive edge.

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IBM Data Science in Practice

APRIL 4, 2023

Introduction This article shows how to monitor a model deployed on AWS Sagemaker for quality, bias and explainability, using IBM Watson OpenScale on the IBM Cloud Pak for Data platform. This article shows how to use the endpoint generated from that tutorial to demonstrate how to monitor the AWS deployment with Watson OpenScale.

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AWS Machine Learning Blog

APRIL 29, 2024

For AWS and Outerbounds customers, the goal is to build a differentiated machine learning and artificial intelligence (ML/AI) system and reliably improve it over time. First, the AWS Trainium accelerator provides a high-performance, cost-effective, and readily available solution for training and fine-tuning large models.

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AWS Machine Learning Blog

DECEMBER 4, 2024

At AWS re:Invent 2024, we are excited to introduce Amazon Bedrock Marketplace. Through Bedrock Marketplace, organizations can use Nemotron’s advanced capabilities while benefiting from the scalable infrastructure of AWS and NVIDIA’s robust technologies. Li held data science roles in the financial and retail industries.

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AWS Machine Learning Blog

APRIL 26, 2023

Do you need help to move your organization’s Machine Learning (ML) journey from pilot to production? Most executives think ML can apply to any business decision, but on average only half of the ML projects make it to production. Challenges Customers may face several challenges when implementing machine learning (ML) solutions.

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AWS Machine Learning Blog

OCTOBER 11, 2024

Since our founding nearly two decades ago, machine learning (ML) and artificial intelligence (AI) have been at the heart of building data-driven products that better match job seekers with the right roles and get people hired. He loves solving big problems and innovating with how Indeed gets value from data.

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AWS Machine Learning Blog

SEPTEMBER 18, 2024

The ZMP analyzes billions of structured and unstructured data points to predict consumer intent by using sophisticated artificial intelligence (AI) to personalize experiences at scale. Hosted on Amazon ECS with tasks run on Fargate, this platform streamlines the end-to-end ML workflow, from data ingestion to model deployment.

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AWS Machine Learning Blog

DECEMBER 4, 2023

In this post, we explain how we built an end-to-end product category prediction pipeline to help commercial teams by using Amazon SageMaker and AWS Batch , reducing model training duration by 90%. An important aspect of our strategy has been the use of SageMaker and AWS Batch to refine pre-trained BERT models for seven different languages.

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AWS Machine Learning Blog

DECEMBER 7, 2023

In this post, we describe the end-to-end workforce management system that begins with location-specific demand forecast, followed by courier workforce planning and shift assignment using Amazon Forecast and AWS Step Functions. AWS Step Functions automatically initiate and monitor these workflows by simplifying error handling.

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AWS Machine Learning Blog

MAY 30, 2024

In this post, we introduce the Media Analysis and Policy Evaluation solution, which uses AWS AI and generative AI services to provide a framework to streamline video extraction and evaluation processes. This solution, powered by AWS AI and generative AI services, meets these needs.

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