AWS Machine Learning Blog

DECEMBER 4, 2024

This integration addresses these hurdles by providing data scientists and ML engineers with a comprehensive environment that supports the entire ML lifecycle, from development to deployment at scale. In this post, we walk you through the process of scaling your ML workloads using SageMaker Studio and SageMaker HyperPod.

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DataRobot

DECEMBER 12, 2019

Back in 2012, Harvard Business Review called data scientists “the sexiest job of the 21st century.” That may or may not be true, but I do believe that one of the hardest jobs in the latter half of this decade is that of the executive responsible for developing and implementing AI strategy in the enterprise.

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Towards AI

MARCH 14, 2024

There are so many questions you guys have been asking me, so in this blog post, I thought I would try to answer them and share the three best ways to achieve your goal of getting a data science job.And, since there is no simple answer, it’s really important to have a look at all three methods so that I can help you pick the best choice for yourself!

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AWS Machine Learning Blog

MARCH 13, 2024

To develop models for such use cases, data scientists need access to various datasets like credit decision engines, customer transactions, risk appetite, and stress testing. This post walks through the steps involved in configuring S3 Access Points to enable cross-account access from a SageMaker notebook instance.

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Pickl AI

APRIL 28, 2023

With more than 650% growth since 2012, Data Science has emerged as one of the most sought-after technologies. With the new developments in this domain, Data Science presents a picture of futuristic technology. A Data Scientist’s average salary in India is up to₹ 8.0 Data Scientist Salary in Hyderabad : ₹ 8.0

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AWS Machine Learning Blog

SEPTEMBER 23, 2024

Launched in 2021, Amazon SageMaker Canvas is a visual point-and-click service that allows business analysts and citizen data scientists to use ready-to-use machine learning (ML) models and build custom ML models to generate accurate predictions without writing any code. This is crucial for compliance, security, and governance.

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AWS Machine Learning Blog

JUNE 6, 2025

Organizations building or adopting generative AI use GPUs to run simulations, run inference (both for internal or external usage), build agentic workloads, and run data scientists’ experiments. The workloads range from ephemeral single-GPU experiments run by scientists to long multi-node continuous pre-training runs.

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DataRobot

JUNE 18, 2019

In 2012, DataRobot co-founders Jeremy Achin and Tom de Godoy recognized the profound impact that AI and machine learning could have on organizations, but that there wouldn’t be enough data scientists to meet the demand.

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AWS Machine Learning Blog

MARCH 15, 2023

We demonstrate how two different personas, a data scientist and an MLOps engineer, can collaborate to lift and shift hundreds of legacy models. We assume the involvement of two personas: a data scientist and an MLOps engineer. You can easily extend this solution to add more functionality.

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AWS Machine Learning Blog

SEPTEMBER 27, 2024

Ref S3BucketName, '/*']] - PolicyName: SNSPublish PolicyDocument: Version: '2012-10-17' Statement: - Effect: Allow Action: - 'sns:Publish' Resource: !Ref Ref S3BucketName, '/*']] - PolicyName: SNSPublish PolicyDocument: Version: '2012-10-17' Statement: - Effect: Allow Action: - 'sns:Publish' Resource: !Ref Join ['', ['arn:aws:s3:::',

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AWS Machine Learning Blog

SEPTEMBER 3, 2024

Seamless integration with SageMaker – As a built-in feature of the SageMaker platform, the EMR Serverless integration provides a unified and intuitive experience for data scientists and engineers. By unlocking the potential of your data, this powerful integration drives tangible business results.

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AWS Machine Learning Blog

MAY 1, 2025

About the authors Yanyan Zhang is a Senior Generative AI Data Scientist at Amazon Web Services, where she has been working on cutting-edge AI/ML technologies as a Generative AI Specialist, helping customers use generative AI to achieve their desired outcomes. Happy fine-tuning!

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AWS Machine Learning Blog

JUNE 11, 2025

To learn more about Amazon Bedrock Knowledge Bases, see Retrieve data and generate AI responses with knowledge bases. About the Authors Kamran Razi is a Data Scientist at the Amazon Generative AI Innovation Center. Nay Doummar is an Engineering Manager on the Unified Support team at Adobe, where she’s been since 2012.

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AWS Machine Learning Blog

OCTOBER 28, 2024

For more information, see Query any data source with Amazon Athena’s new federated query and Import data from over 40 data sources for no-code machine learning with Amazon SageMaker Canvas.

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AWS Machine Learning Blog

NOVEMBER 9, 2023

Policy 3 – Attach AWSLambda_FullAccess , which is an AWS managed policy that grants full access to Lambda, Lambda console features, and other related AWS services.

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AWS Machine Learning Blog

MAY 10, 2023

Jupyter notebooks are highly favored by data scientists for their ability to interactively process data, build ML models, and test these models by making inferences on data. However, there are scenarios in which data scientists may prefer to transition from interactive development on notebooks to batch jobs.

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AWS Machine Learning Blog

DECEMBER 4, 2024

SageMaker JumpStart has long been the go-to service for developers and data scientists seeking to deploy state-of-the-art generative AI models. It allows you to use advanced features in Amazon Bedrock such as the playground, guardrails, and tool use (function calling).

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Pickl AI

FEBRUARY 6, 2024

Summary: Are you still wondering whether or not you should pursue your career as a Data Scientist? This blog breaks the ice and unfolds 10 reasons to learn Data Science. 10 reasons to learn Data Science The rapid increase in digitization has created volumes of data. Lakhs Benefits of studying Data Science 1.

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AWS Machine Learning Blog

AUGUST 31, 2023

In addition to data engineers and data scientists, there have been inclusions of operational processes to automate & streamline the ML lifecycle. For more information about improving governance of your ML models, refer to Improve governance of your machine learning models with Amazon SageMaker.

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AWS Machine Learning Blog

SEPTEMBER 19, 2023

Create a role named sm-build-role with the following trust policy, and add the policy sm-build-policy that you created earlier: { "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Principal": { "Service": "codebuild.amazonaws.com" }, "Action": "sts:AssumeRole" } ] } Now, let’s review the steps in CloudShell. base-ubuntu18.04

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ODSC - Open Data Science

FEBRUARY 28, 2023

Taipy brings to bear the experience of veteran data scientists and bridges the gap between data dashboards and full AI applications. Their CDP machine learning allows teams to collaborate across the full data life cycle with scalable computing resources, tools, and more.

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Flipboard

MARCH 7, 2023

The main benefit is that a data scientist can choose which script to run to customize the container with new packages. There are also limited options for ad hoc script customization by users, such as data scientists or ML engineers, due to permissions of the user profile execution role.

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AWS Machine Learning Blog

MAY 8, 2023

Lastly, thanks to SageMaker Studio extensibility, we further improve the data scientist experience by making MLflow accessible within Studio, as shown in the following screenshot. Finally, we demonstrated how to enhance the experience of data scientists by integrating MLflow into Studio through simple extensions.

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Tableau

JUNE 8, 2021

This newly released guide is a toolkit that provides extensive guidance for data scientists, data communications professionals, and everyone who creates or uses visualization tools to prioritize race and equity throughout the entire process. SENIOR DATA SCIENTIST, NATERA. linkedin twitter. Alice Feng.

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AWS Machine Learning Blog

NOVEMBER 15, 2024

Data scientists and developers can quickly prototype and experiment with various ML use cases, accelerating the development and deployment of ML applications. of persons present’ for the sustainability committee meeting held on 5th April, 2012? WASHINGTON, D. 20036 1128 SIXTEENTH ST., WASHINGTON, D. 20036 What is the ‘no.

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O'Reilly Media

SEPTEMBER 19, 2023

But in its early form of a Hadoop-based ML library, Mahout still required data scientists to write in Java. A typical data job interview now skipped MapReduce in favor of white-boarding k-means clustering or random forests. ” There’s as much Keras, TensorFlow, and Torch today as there was Hadoop back in 2010-2012.

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AWS Machine Learning Blog

JUNE 21, 2024

These can be added as inline policies in the user’s IAM role: { "Version": "2012-10-17", "Statement": [ { "Action": "s3:*", "Effect": "Deny", "Resource": [ "arn:aws:s3:::jumpstart-cache-prod- ", "arn:aws:s3:::jumpstart-cache-prod- /*" ], "Condition": { "StringNotLike": {"s3:prefix": ["*.ipynb",

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AWS Machine Learning Blog

OCTOBER 17, 2024

Data scientists and ML engineers can spin up SageMaker Studio private and shared spaces , which are used to manage the storage and resource needs of the JupyterLab and Code Editor applications, enable stopping the applications when not in use to save on compute costs, and resume the work from where they stopped.

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AWS Machine Learning Blog

APRIL 16, 2024

Amazon SageMaker Studio provides a fully managed solution for data scientists to interactively build, train, and deploy machine learning (ML) models. In the process of working on their ML tasks, data scientists typically start their workflow by discovering relevant data sources and connecting to them.

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DataRobot

NOVEMBER 12, 2021

DataRobot was founded in 2012 and today is one of the most widely deployed and proven AI platforms in the market, delivering over a trillion predictions for leading companies around the world. We’ve found that implementing a model requires four general personas to collaborate across the organization.

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AWS Machine Learning Blog

MAY 17, 2023

Many data scientists and business analysts at large oil companies don’t have the necessary skillset to run advanced ML experiments on important tasks such as facies classification. This allows data scientists to review the model in detail, test it, make any changes that may improve accuracy, and share the updated model back with you.

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Alation

JULY 7, 2022

To answer these questions we need to look at how data roles within the job market have evolved, and how academic programs have changed to meet new workforce demands. In the 2010s, the growing scope of the data landscape gave rise to a new profession: the data scientist. The data scientist.

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IBM Journey to AI blog

OCTOBER 12, 2023

These models rely on learning algorithms that are developed and maintained by data scientists. However, AI capabilities have been evolving steadily since the breakthrough development of artificial neural networks in 2012, which allow machines to engage in reinforcement learning and simulate how the human brain processes information.

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AWS Machine Learning Blog

MARCH 10, 2025

With a decade of experience at Amazon, having joined in 2012, Kshitiz has gained deep insights into the cloud computing landscape. Sandeep Singh is a Senior Generative AI Data Scientist at Amazon Web Services, helping businesses innovate with generative AI. He specializes in generative AI, machine learning, and system design.

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Smart Data Collective

OCTOBER 17, 2022

In fact, you may have even heard about IDC’s new Global DataSphere Forecast, 2021-2025 , which projects that global data production and replication will expand at a compound annual growth rate of 23% during the projection period, reaching 181 zettabytes in 2025. zettabytes of data in 2020, a tenfold increase from 6.5

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Pickl AI

DECEMBER 14, 2023

Through this blog, we take you through the prerequisites of mathematics for Data science and other skills that will make you a successful Data scientist. Why Data Science? Well, before digging deeper into the prerequisites for Data science, let’s have a quick understanding of why Data Science is gaining popularity.

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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. The following diagram illustrates the architecture of the FL setup on SageMaker with the Flower package.

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