AWS Machine Learning Blog

AUGUST 28, 2023

As part of the 2023 Data Science Conference (DSCO 23), AWS partnered with the Data Institute at the University of San Francisco (USF) to conduct a datathon. During the datathon, my team member and I conducted research on different ML models (LightGBM, logistic regression, SVM models, Random Forest Classifier, etc.)

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AWS Machine Learning Blog

AUGUST 26, 2024

At AWS, we are transforming our seller and customer journeys by using generative artificial intelligence (AI) across the sales lifecycle. It will be able to answer questions, generate content, and facilitate bidirectional interactions, all while continuously using internal AWS and external data to deliver timely, personalized insights.

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The MLOps Blog

JUNE 27, 2023

As you delve into the landscape of MLOps in 2023, you will find a plethora of tools and platforms that have gained traction and are shaping the way models are developed, deployed, and monitored. For example, if you use AWS, you may prefer Amazon SageMaker as an MLOps platform that integrates with other AWS services.

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AWS Machine Learning Blog

SEPTEMBER 27, 2024

We can also gain an understanding of data presented in charts and graphs by asking questions related to business intelligence (BI) tasks, such as “What is the sales trend for 2023 for company A in the enterprise market?” AWS Fargate is the compute engine for web application. This allows you to experiment quickly with new designs.

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AWS Machine Learning Blog

FEBRUARY 6, 2024

QnABot on AWS is an open source solution built using AWS native services like Amazon Lex , Amazon OpenSearch Service , AWS Lambda , Amazon Transcribe , and Amazon Polly. According to Gartner Magic Quadrant 2023, ServiceNow is one of the leading IT Service Management (ITSM) providers on the market. QnABot version 5.4+

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AWS Machine Learning Blog

MAY 23, 2023

The seeds of a machine learning (ML) paradigm shift have existed for decades, but with the ready availability of virtually infinite compute capacity, a massive proliferation of data, and the rapid advancement of ML technologies, customers across industries are rapidly adopting and using ML technologies to transform their businesses.

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AWS Machine Learning Blog

DECEMBER 24, 2024

To simplify infrastructure setup and accelerate distributed training, AWS introduced Amazon SageMaker HyperPod in late 2023. In this blog post, we showcase how you can perform efficient supervised fine tuning for a Meta Llama 3 model using PEFT on AWS Trainium with SageMaker HyperPod. architectures/5.sagemaker-hyperpod/LifecycleScripts/base-config/

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AWS Machine Learning Blog

MAY 14, 2024

RLHF is a technique that combines rewards and comparisons, with human feedback to pre-train or fine-tune a machine learning (ML) model. We present the solution and provide an example by simulating a case where the tier one AWS experts are notified to help customers using a chat-bot.

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Towards AI

AUGUST 18, 2023

Last Updated on August 19, 2023 by Editorial Team Author(s): Paul Iusztin Originally published on Towards AI. Terraform 101: How to Use Terraform as an MLE to Automate a Production-Ready AWS Infrastructure This member-only story is on us. Upgrade to access all of Medium. without making even one manual click!

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Dataconomy

FEBRUARY 6, 2024

With the ability to analyze a vast amount of data in real-time, identify patterns, and detect anomalies, AI/ML-powered tools are enhancing the operational efficiency of businesses in the IT sector. Why does AI/ML deserve to be the future of the modern world? Let’s understand the crucial role of AI/ML in the tech industry.

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Mlearning.ai

FEBRUARY 26, 2023

AWS is teaming up with Udacity to award 2,500 students with scholarships in 2023. Continue reading on MLearning.ai »

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AWS Machine Learning Blog

NOVEMBER 15, 2023

In this post, we demonstrate how data aggregated within the AWS CCI Post Call Analytics solution allowed Principal to gain visibility into their contact center interactions, better understand the customer journey, and improve the overall experience between contact channels while also maintaining data integrity and security.

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AWS Machine Learning Blog

APRIL 10, 2023

You don’t have to be an expert in machine learning (ML) to appreciate the value of large language models (LLMs). ML practitioners keep improving the accuracy and capabilities of these models. In this post, we take the same approach but host the model on AWS Inferentia2. This is particularly useful for large language models.

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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. In 2023, SageMaker announced the release of the new SageMaker Studio, which offers two new types of applications: JupyterLab and Code Editor.

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IBM Journey to AI blog

MARCH 14, 2024

The solution: IBM databases on AWS To solve for these challenges, IBM’s portfolio of SaaS database solutions on Amazon Web Services (AWS), enables enterprises to scale applications, analytics and AI across the hybrid cloud landscape. Let’s delve into the database portfolio from IBM available on AWS. 

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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. We pick the first week of December 2023 in this example. This way, our analysis is based on clear and reliable imagery.

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AWS Machine Learning Blog

APRIL 20, 2023

Each machine learning (ML) system has a unique service level agreement (SLA) requirement with respect to latency, throughput, and cost metrics. Based on Inference Recommender’s instance type recommendations, we can find the right real-time serving ML instances that yield the right price-performance for this use case.

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Flipboard

NOVEMBER 20, 2023

In SageMaker Studio, the integrated development environment (IDE) purpose-built for ML, you can launch notebooks that run on different instance types and with different configurations, collaborate with colleagues, and access additional purpose-built features for machine learning (ML). embeddings.

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Towards AI

APRIL 4, 2023

Last Updated on April 4, 2023 by Editorial Team Introducing a Python SDK that allows enterprises to effortlessly optimize their ML models for edge devices. With their groundbreaking web-based Studio platform, engineers have been able to collect data, develop and tune ML models, and deploy them to devices.

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Towards AI

JUNE 24, 2023

Last Updated on June 28, 2023 by Editorial Team Author(s): Anirudh Mehta Originally published on Towards AI. The ’31 Questions that Shape Fortune 500 ML Strategy’ highlighted key questions to assess the maturity of an ML system. A robust ML platform offers managed solutions to easily address these aspects.

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AWS Machine Learning Blog

MAY 7, 2024

Based on a survey conducted by American Express in 2023, 41% of business meetings are expected to take place in hybrid or virtual format by 2024. Hugging Face is an open-source machine learning (ML) platform that provides tools and resources for the development of AI projects.

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AWS Machine Learning Blog

JULY 26, 2023

Generative AI Foundations on AWS is a new technical deep dive course that gives you the conceptual fundamentals, practical advice, and hands-on guidance to pre-train, fine-tune, and deploy state-of-the-art foundation models on AWS and beyond. Feel free to reach out to me on Medium, LinkedIn , GitHub , or through your AWS teams.

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IBM Journey to AI blog

MAY 26, 2023

The role of AWS and cloud security in life sciences However, with greater power comes great responsibility. Most life sciences companies are raising their security posture with AWS infrastructure and services. Organizations like Moderna and Bristol Myers Squibb have chosen AWS to run their regulated workloads.

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AWS Machine Learning Blog

DECEMBER 12, 2024

The machine learning (ML) practitioners need to iterate over these settings before finally deploying the endpoint to SageMaker for inference. Over the past 5 years, she has worked with multiple enterprise customers to set up a secure, scalable AI/ML platform built on SageMaker.

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AWS Machine Learning Blog

APRIL 2, 2024

SageMaker JumpStart is the machine learning (ML) hub of SageMaker that provides access to foundation models in addition to built-in algorithms to help you quickly get started with ML. In December 2023, the Solar 10.7B This model requires an AWS Marketplace subscription. What’s the Solar model? times faster.

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AWS Machine Learning Blog

DECEMBER 4, 2024

Businesses are under pressure to show return on investment (ROI) from AI use cases, whether predictive machine learning (ML) or generative AI. Only 54% of ML prototypes make it to production, and only 5% of generative AI use cases make it to production. Using SageMaker, you can build, train and deploy ML models.

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AWS Machine Learning Blog

MARCH 1, 2024

At AWS re:Invent 2023, we announced the general availability of Knowledge Bases for Amazon Bedrock. To show you an example of switching between hybrid and semantic (vector) search options, we have created a knowledge base using the Amazon 10K document for 2023. billion for 2021, 2022, and 2023. billion, $6.1 billion, $6.1

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AWS Machine Learning Blog

JULY 24, 2023

In this post we walk you through the process of deploying FastAPI model servers on AWS Inferentia devices (found on Amazon EC2 Inf1 and Amazon EC Inf2 instances). Each AWS Inferentia1 device contains four NeuronCores-v1 and each AWS Inferentia2 device contains two NeuronCores-v2. For example, NEURON_RT_NUM_CORES=2 myapp.py

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ODSC - Open Data Science

FEBRUARY 17, 2023

NLP Skills for 2023 These skills are platform agnostic, meaning that employers are looking for specific skillsets, expertise, and workflows. TensorFlow is desired for its flexibility for ML and neural networks, PyTorch for its ease of use and innate design for NLP, and scikit-learn for classification and clustering.

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AWS Machine Learning Blog

MARCH 15, 2024

This approach can help heart stroke patients, doctors, and researchers with faster diagnosis, enriched decision-making, and more informed, inclusive research work on stroke-related health issues, using a cloud-native approach with AWS services for lightweight lift and straightforward adoption. Stroke victims can lose around 1.9

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AWS Machine Learning Blog

APRIL 19, 2024

We used AWS services including Amazon Bedrock , Amazon SageMaker , and Amazon OpenSearch Serverless in this solution. In this series, we use the slide deck Train and deploy Stable Diffusion using AWS Trainium & AWS Inferentia from the AWS Summit in Toronto, June 2023 to demonstrate the solution.

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AWS Machine Learning Blog

JUNE 18, 2024

On December 6 th -8 th 2023, the non-profit organization, Tech to the Rescue , in collaboration with AWS, organized the world’s largest Air Quality Hackathon – aimed at tackling one of the world’s most pressing health and environmental challenges, air pollution. As always, AWS welcomes your feedback.

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ODSC - Open Data Science

FEBRUARY 2, 2023

The role of a data scientist is in demand and 2023 will be no exception. To get a better grip on those changes we reviewed over 25,000 data scientist job descriptions from that past year to find out what employers are looking for in 2023. However, each year the skills and certainly the platforms change somewhat.

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ODSC - Open Data Science

MARCH 27, 2023

Learn about the flow, difficulties, and tools for performing ML clustering at scale Ori Nakar | Principal Engineer, Threat Research | Imperva Given that there are billions of daily botnet attacks from millions of different IPs, the most difficult challenge of botnet detection is choosing the most relevant data.

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AWS Machine Learning Blog

AUGUST 4, 2023

Amazon SageMaker Data Wrangler reduces the time it takes to aggregate and prepare tabular and image data for machine learning (ML) from weeks to minutes. You can build an ML model with SageMaker Autopilot representing all your data using the manifest file and use that for your ML inference and production deployment.

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AWS Machine Learning Blog

MAY 22, 2024

Using machine learning (ML) and natural language processing (NLP) to automate product description generation has the potential to save manual effort and transform the way ecommerce platforms operate. For details, see Creating an AWS account. Note: Be sure to set up your AWS Command Line Interface (AWS CLI) credentials correctly.

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AWS Machine Learning Blog

NOVEMBER 26, 2023

Amazon Personalize is excited to announce the new Next Best Action ( aws-next-best-action ) recipe to help you determine the best actions to suggest to your individual users that will enable you to increase brand loyalty and conversion. All your data is encrypted to be private and secure.

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