AWS Machine Learning Blog

JANUARY 30, 2025

The AWS Social Responsibility & Impact (SRI) team recognized an opportunity to augment this function using generative AI. Historically, AWS Health Equity Initiative applications were reviewed manually by a review committee. It took 14 or more days each cycle for all applications to be fully reviewed.

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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%. This capability of predictive analytics, particularly the accurate forecast of product categories, has proven invaluable.

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Data Science Dojo

OCTOBER 31, 2024

Familiarity with data preprocessing, feature engineering, and model evaluation techniques is crucial. Additionally, knowledge of cloud platforms (AWS, Google Cloud) and experience with deployment tools (Docker, Kubernetes) are highly valuable.

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AWS Machine Learning Blog

AUGUST 21, 2023

You can streamline the process of feature engineering and data preparation with SageMaker Data Wrangler and finish each stage of the data preparation workflow (including data selection, purification, exploration, visualization, and processing at scale) within a single visual interface. Choose Create stack.

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Dataconomy

SEPTEMBER 4, 2023

Text analytics is crucial for sentiment analysis, content categorization, and identifying emerging trends. Big data analytics: Big data analytics is designed to handle massive volumes of data from various sources, including structured and unstructured data.

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Pickl AI

FEBRUARY 10, 2025

Summary: This blog provides an in-depth look at the top 20 AWS interview questions, complete with detailed answers. Covering essential topics such as EC2, S3, security, and cost optimization, this guide is designed to equip candidates with the knowledge needed to excel in AWS-related interviews and advance their careers in cloud computing.

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Data Science Dojo

JULY 6, 2023

Amazon Redshift: Amazon Redshift is a cloud-based data warehousing service provided by Amazon Web Services (AWS). Amazon Redshift allows data engineers to analyze large datasets quickly using massively parallel processing (MPP) architecture. It is known for its high performance and cost-effectiveness.

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AWS Machine Learning Blog

FEBRUARY 13, 2024

SageMaker Feature Store now makes it effortless to share, discover, and access feature groups across AWS accounts. With this launch, account owners can grant access to select feature groups by other accounts using AWS Resource Access Manager (AWS RAM). Review the access policy to understand permissions granted.

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AWS Machine Learning Blog

NOVEMBER 8, 2023

It is available as part of the Toolkit for Visual Studio Code , AWS Cloud9 , JupyterLab, Amazon SageMaker Studio , AWS Lambda , AWS Glue , and JetBrains IntelliJ IDEA. Impact of unoptimized code on cloud computing and application carbon footprint AWS’s infrastructure is 3.6

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AWS Machine Learning Blog

SEPTEMBER 3, 2024

Scalability and performance – The EMR Serverless integration automatically scales the compute resources up or down based on your workload’s demands, making sure you always have the necessary processing power to handle your big data tasks. This same interface is also used for provisioning EMR clusters.

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AWS Machine Learning Blog

MARCH 3, 2023

With faster model training times, you can focus on understanding your data and analyzing the impact of the data, and achieve effective business outcomes. This capability is available in all AWS regions where SageMaker Canvas is now supported. About the Authors Ajjay Govindaram is a Senior Solutions Architect at AWS.

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Pickl AI

DECEMBER 26, 2024

Each platform offers unique capabilities tailored to varying needs, making the platform a critical decision for any Data Science project. Major Cloud Platforms for Data Science Amazon Web Services ( AWS ), Microsoft Azure, and Google Cloud Platform (GCP) dominate the cloud market with their comprehensive offerings.

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AWS Machine Learning Blog

AUGUST 21, 2024

Amazon DataZone is a data management service that makes it quick and convenient to catalog, discover, share, and govern data stored in AWS, on-premises, and third-party sources. An Amazon DataZone domain and an associated Amazon DataZone project configured in your AWS account.

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Flipboard

JUNE 18, 2023

Snowflake (NYSE:SNOW) originally built their cloud-based warehouse on AWS in 2014, then started to build their platform and applications to operate …

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AWS Machine Learning Blog

NOVEMBER 29, 2023

With its comprehensive data preparation and unified experience from data to insights, SageMaker Canvas empowers you to improve your ML outcomes. For more information on how to accelerate your journeys from data to business insights, see SageMaker Canvas immersion day and AWS user guide. Product Manager at AWS.

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AWS Machine Learning Blog

MARCH 10, 2023

For each option, we deploy a unique stack of AWS CloudFormation templates. For the EMR cluster, connects the AWS Glue Data Catalog as metastore for EMR Hive and Presto, creates a Hive table in EMR, and fills it with data from a US airport dataset. Open the Amazon S3 page by searching for S3 in the AWS console search.

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IBM Journey to AI blog

AUGUST 23, 2023

When it comes to hosting applications on Amazon Web Services (AWS), one of the most important decisions you will need to make is which Amazon Elastic Compute Cloud (EC2) instance type to choose. EC2 instances are virtual machines that allow you to run your applications on AWS.

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Flipboard

MARCH 22, 2023

In this post, we show how to configure a new OAuth-based authentication feature for using Snowflake in Amazon SageMaker Data Wrangler. Snowflake is a cloud data platform that provides data solutions for data warehousing to data science. For more information about prerequisites, see Get Started with Data Wrangler.

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AWS Machine Learning Blog

JUNE 3, 2024

based single sign-on (SSO) methods, such as AWS IAM Identity Center. To learn more, see Secure access to Amazon SageMaker Studio with AWS SSO and a SAML application. For Data flow name , enter a name (for example, AssessingMentalHealthFlow ). SageMaker Data Wrangler will open. You can also use your organization’s SAML 2.0-based

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AWS Machine Learning Blog

MAY 3, 2023

Furthermore, the dynamic nature of a customer’s data can also result in a large variance of the processing time and resources required to optimally complete the feature engineering. AWS customer Vericast is a marketing solutions company that makes data-driven decisions to boost marketing ROIs for its clients.

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AWS Machine Learning Blog

AUGUST 22, 2023

With SageMaker, data scientists and developers can quickly build and train ML models, and then deploy them into a production-ready hosted environment. In this post, we demonstrate how to use the managed ML platform to provide a notebook experience environment and perform federated learning across AWS accounts, using SageMaker training jobs.

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AWS Machine Learning Blog

MAY 10, 2023

Prerequisites The following prerequisites are needed to implement this solution: An AWS account with permissions to create AWS Identity and Access Management (IAM) policies and roles. About the Authors Ajjay Govindaram is a Senior Solutions Architect at AWS. Varun Mehta is a Solutions Architect at AWS.

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Data Science Dojo

JULY 3, 2024

Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. Data Processing and Analysis : Techniques for data cleaning, manipulation, and analysis using libraries such as Pandas and Numpy in Python.

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AWS Machine Learning Blog

MAY 15, 2023

We outline how we built an automated demand forecasting pipeline using Forecast and orchestrated by AWS Step Functions to predict daily demand for SKUs. On an ongoing basis, we calculate mean absolute percentage error (MAPE) ratios with product-based data, and optimize model and feature ingestion processes.

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Flipboard

MARCH 7, 2023

You can manage app images via the SageMaker console, the AWS SDK for Python (Boto3), and the AWS Command Line Interface (AWS CLI). The Studio Image Build CLI lets you build SageMaker-compatible Docker images directly from your Studio environments by using AWS CodeBuild. Environments without internet access.

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AWS Machine Learning Blog

NOVEMBER 27, 2023

Upload embedding to a vector database (powered by OpenSearch) Prerequisites For this walkthrough, you should have the following: An AWS account with permissions to create AWS Identity and Access Management (AWS IAM) policies and roles Access to Amazon SageMaker , an instance of Amazon SageMaker Studio , and a user for Studio.

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ODSC - Open Data Science

FEBRUARY 6, 2024

LLMs Meet Google Cloud: A New Frontier in Big Data Analytics Mohammad Soltanieh-ha, PhD | Clinical Assistant Professor | Boston University Dive into the world of cloud computing and big data analytics with Google Cloud’s advanced tools and big data capabilities.

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IBM Journey to AI blog

FEBRUARY 6, 2024

Internet companies like Amazon led the charge with the introduction of Amazon Web Services (AWS) in 2002, which offered businesses cloud-based storage and computing services, and the launch of Elastic Compute Cloud (EC2) in 2006, which allowed users to rent virtual computers to run their own applications. Google Workspace, Salesforce).

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Pickl AI

SEPTEMBER 18, 2024

Read More: How Airbnb Uses Big Data and Machine Learning to Offer World-Class Service Netflix’s Big Data Infrastructure Netflix’s data infrastructure is one of the most sophisticated globally, built primarily on cloud technology. petabytes of data. How Does Netflix Ensure Security Against Fraud?

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IBM Journey to AI blog

DECEMBER 20, 2023

AWS, Google Cloud Services, IBM Cloud, Microsoft Azure) makes computing resources—like ready-to-use software applications, virtual machines (VMs) , enterprise-grade infrastructures and development platforms—available to users over the public internet. virtual machines, databases, applications, microservices and nodes).

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Pickl AI

MARCH 11, 2025

Cloud Computing provides scalable infrastructure for data storage, processing, and management. Both technologies complement each other by enabling real-time analytics and efficient data handling. Cloud platforms like AWS and Azure support Big Data tools, reducing costs and improving scalability.

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ODSC - Open Data Science

OCTOBER 22, 2024

Snowflake: Known for its cloud-based data warehousing solutions, enabling efficient big data analytics. Dataiku: Providing an end-to-end data science and machine learning platform for enterprises. SAS: A long-standing leader in analytics software and services.

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Pickl AI

JULY 20, 2023

Defining clear objectives and selecting appropriate techniques to extract valuable insights from the data is essential. Here are some project ideas suitable for students interested in big data analytics with Python: 1.

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Pickl AI

APRIL 6, 2023

Consequently, here is an overview of the essential requirements that you need to have to get a job as an Azure Data Engineer. In-depth knowledge of distributed systems like Hadoop and Spart, along with computing platforms like Azure and AWS. Which service would you use to create Data Warehouse in Azure?

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Pickl AI

JANUARY 30, 2025

Careful planning mitigates data skew, debugging complexities, and memory constraints. Embracing MapReduce ensures fault tolerance, faster insights, and cost-effective big data analytics. You can easily create and manage your cluster without worrying about on-premises hardware.

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IBM Journey to AI blog

SEPTEMBER 4, 2024

Speed Kafka’s data processing system uses APIs in a unique way that help it to optimize data integration to many other database storage designs, such as the popular SQL and NoSQL architectures , used for big data analytics.

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Pickl AI

OCTOBER 11, 2024

Indian Context: Growing Need for Robust DBMS Solutions In India’s rapidly evolving digital landscape—where businesses are increasingly adopting technologies like cloud computing and big Data Analytics—the importance of robust DBMS architecture is amplified.

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