Analytics Vidhya

DECEMBER 30, 2022

This article was published as a part of the Data Science Blogathon. Introduction In machine learning, the data is an essential part of the training of machine learning algorithms. The amount of data and the data quality highly affect the results from the machine learning algorithms.

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AWS Machine Learning Blog

OCTOBER 5, 2023

In this post, we walk through how to fine-tune Llama 2 on AWS Trainium , a purpose-built accelerator for LLM training, to reduce training times and costs. We review the fine-tuning scripts provided by the AWS Neuron SDK (using NeMo Megatron-LM), the various configurations we used, and the throughput results we saw.

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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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AWS Machine Learning Blog

DECEMBER 12, 2023

In this post, we’ll summarize training procedure of GPT NeoX on AWS Trainium , a purpose-built machine learning (ML) accelerator optimized for deep learning training. M tokens/$) trained such models with AWS Trainium without losing any model quality. We’ll outline how we cost-effectively (3.2 billion in Pythia.

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Analytics Vidhya

MAY 16, 2022

This article was published as a part of the Data Science Blogathon. Introduction on Amazon Elasticsearch Service Amazon Elasticsearch Service is a powerful tool that allows you to perform a number of functions. Let us examine how this powerful tool works behind the scenes.

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AWS Machine Learning Blog

MARCH 15, 2024

The need for federated learning in healthcare Healthcare relies heavily on distributed data sources to make accurate predictions and assessments about patient care. Limiting the available data sources to protect privacy negatively affects result accuracy and, ultimately, the quality of patient care.

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AWS Machine Learning Blog

NOVEMBER 19, 2024

The excitement is building for the fourteenth edition of AWS re:Invent, and as always, Las Vegas is set to host this spectacular event. The sessions showcase how Amazon Q can help you streamline coding, testing, and troubleshooting, as well as enable you to make the most of your data to optimize business operations.

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AWS Machine Learning Blog

MAY 23, 2023

In April 2023, AWS unveiled Amazon Bedrock , which provides a way to build generative AI-powered apps via pre-trained models from startups including AI21 Labs , Anthropic , and Stability AI. Amazon Bedrock also offers access to Titan foundation models, a family of models trained in-house by AWS. Deploy the AWS CDK application.

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AWS Machine Learning Blog

JUNE 11, 2024

Sprinklr’s specialized AI models streamline data processing, gather valuable insights, and enable workflows and analytics at scale to drive better decision-making and productivity. During this journey, we collaborated with our AWS technical account manager and the Graviton software engineering teams.

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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.

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AWS Machine Learning Blog

SEPTEMBER 3, 2024

By using the Livy REST APIs , SageMaker Studio users can also extend their interactive analytics workflows beyond just notebook-based scenarios, enabling a more comprehensive and streamlined data science experience within the Amazon SageMaker ecosystem. This same interface is also used for provisioning EMR clusters.

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AWS Machine Learning Blog

OCTOBER 24, 2024

Conventional ML development cycles take weeks to many months and requires sparse data science understanding and ML development skills. Business analysts’ ideas to use ML models often sit in prolonged backlogs because of data engineering and data science team’s bandwidth and data preparation activities.

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AWS Machine Learning Blog

FEBRUARY 2, 2024

Because embeddings are an important source of data for NLP models in general and generative AI solutions in particular, we need a way to measure whether our embeddings are changing over time (drifting). Then we use K-Means to identify a set of cluster centers.

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Becoming Human

MAY 15, 2023

Data Science is a popular as well as vast field; till date, there are a lot of opportunities in this field, and most people, whether they are working professionals or students, everyone want a transition in data science because of its scope. How much to learn? What to do next?

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AWS Machine Learning Blog

SEPTEMBER 14, 2023

The SageMaker Python SDK automatically translates your existing workspace environment, and any associated data processing code and datasets, into an SageMaker training job that runs on the training platform. For details, refer to Creating an AWS account. In this post, we use Amazon SageMaker Studio with the Data Science 3.0

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AWS Machine Learning Blog

MAY 1, 2024

Our unstructured data comes from the Amazon EC2 User Guide for Linux Instances and Amazon EC2 Instance Types documentation, and the structured data is derived from the EC2 Instance On-Demand Pricing for the US East (N. Virginia) AWS Region. file for deploying the solution using the AWS CDK. xlarge instance to $24.78

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Flipboard

AUGUST 17, 2023

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and ML to deliver the best price-performance at any scale. To do this, we provide an AWS CloudFormation template to create a stack that contains the resources.

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AWS Machine Learning Blog

DECEMBER 29, 2022

However, working with data in the cloud can present challenges, such as the need to remove organizational data silos, maintain security and compliance, and reduce complexity by standardizing tooling. AWS offers tools such as RStudio on SageMaker and Amazon Redshift to help tackle these challenges. 1 Public subnet. 1 NAT gateway.

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AWS Machine Learning Blog

MARCH 30, 2023

The match-related data is collected and ingested using DFL’s DataHub. Metadata of the match is processed within the AWS Lambda function MetaDataIngestion , while positional data is ingested using the AWS Fargate container called MatchLink. Tareq Haschemi is a consultant within AWS Professional Services.

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Mlearning.ai

MAY 23, 2023

While specific requirements may vary depending on the organization and the role, here are the key skills and educational background that are required for entry-level data scientists — Skillset Mathematical and Statistical Foundation Data science heavily relies on mathematical and statistical concepts.

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ODSC - Open Data Science

FEBRUARY 17, 2023

The chart below shows 20 in-demand skills that encompass both NLP fundamentals and broader data science expertise. In a change from last year, there’s also a higher demand for those with data analysis skills as well. Having mastery of these two will prove that you know data science and in turn, NLP.

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AWS Machine Learning Blog

OCTOBER 2, 2024

In this post, we share AWS guidance that we have learned and developed as part of real-world projects into practical guides oriented towards the AWS Well-Architected Framework , which is used to build production infrastructure and applications on AWS. To learn more, see Log Amazon Bedrock API calls using AWS CloudTrail.

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Data Science Dojo

JULY 24, 2023

Each node is capable of processing and storing data independently. Clusters : Clusters are groups of interconnected nodes that work together to process and store data. Clustering allows for improved performance and fault tolerance as tasks can be distributed across nodes.

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AWS Machine Learning Blog

NOVEMBER 16, 2023

This is a joint blog with AWS and Philips. Since 2014, the company has been offering customers its Philips HealthSuite Platform, which orchestrates dozens of AWS services that healthcare and life sciences companies use to improve patient care.

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AWS Machine Learning Blog

APRIL 17, 2023

In conjunction with tools like RStudio on SageMaker, users are analyzing, transforming, and preparing large amounts of data as part of the data science and ML workflow. Data scientists and data engineers use Apache Spark, Hive, and Presto running on Amazon EMR for large-scale data processing.

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Data Science Dojo

JULY 6, 2023

It supports various data types and offers advanced features like data sharing and multi-cluster warehouses. Amazon Redshift: Amazon Redshift is a cloud-based data warehousing service provided by Amazon Web Services (AWS). It is known for its high performance and cost-effectiveness.

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AWS Machine Learning Blog

JANUARY 13, 2023

Because they’re in a highly regulated domain, HCLS partners and customers seek privacy-preserving mechanisms to manage and analyze large-scale, distributed, and sensitive data. To mitigate these challenges, we propose a federated learning (FL) framework, based on open-source FedML on AWS, which enables analyzing sensitive HCLS data.

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ODSC - Open Data Science

APRIL 24, 2023

Botnet Detection at Scale — Lessons Learned From Clustering Billions of Web Attacks Into Botnets Editor’s note: Ori Nakar is a speaker for ODSC Europe this June. Be sure to check out his talk, “ Botnet detection at scale — Lesson learned from clustering billions of web attacks into botnets ,” there!

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AWS Machine Learning Blog

FEBRUARY 13, 2024

Augmenting the training data using techniques like cropping, rotating, and flipping images helped improve the model training data and model accuracy. Model training was accelerated by 50% through the use of the SMDDP library, which includes optimized communication algorithms designed specifically for AWS infrastructure.

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Data Science Dojo

AUGUST 24, 2023

When the ML lifecycle is not properly streamlined with MLOps, organizations face issues such as inconsistent results due to varying data quality, slower deployment as manual processes become bottlenecks, and difficulty maintaining and updating models rapidly enough to react to changing business conditions.

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ODSC - Open Data Science

MARCH 27, 2023

Botnets Detection at Scale — Lesson Learned from Clustering Billions of Web Attacks into Botnets. Originally posted on OpenDataScience.com Read more data science articles on OpenDataScience.com , including tutorials and guides from beginner to advanced levels!

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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. The data is sent to the Amazon Titan Text Embeddings model to generate embeddings. Use AWS CloudFormation to create the solution stack You can use AWS CloudFormation to create the solution stack.

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AWS Machine Learning Blog

APRIL 24, 2024

With AWS generative AI services like Amazon Bedrock , developers can create systems that expertly manage and respond to user requests. It is hosted on Amazon Elastic Container Service (Amazon ECS) with AWS Fargate , and it is accessed using an Application Load Balancer. It serves as the data source to the knowledge base.

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Dataconomy

APRIL 28, 2023

Machine learning deployment is a crucial step in bringing the benefits of data science to real-world applications. With the increasing demand for machine learning deployment, various tools and platforms have emerged to help data scientists and developers deploy their models quickly and efficiently.

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AWS Machine Learning Blog

DECEMBER 15, 2023

You want to gather insights on this data and build an ML model to predict how new restaurants will be rated, but find it challenging to perform analytics on unstructured data. You encounter bottlenecks because you need to rely on data engineering and data science teams to accomplish these goals.

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AWS Machine Learning Blog

DECEMBER 13, 2024

Moreover, they require a pre-determined number of topics, which was hard to determine in our data set. The approach uses three sequential BERTopic models to generate the final clustering in a hierarchical method. In this scenario, input data comes from various areas and is usually inputted manually. amazonaws.com/{2}:{3}".format(account_id,

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AWS Machine Learning Blog

NOVEMBER 3, 2023

Match-related data is gathered and brought into the system via DFL’s DataHub. To process match metadata, we use an AWS Lambda function called MetaDataIngestion , while positional data is brought in using an AWS Fargate container known as MatchLink.

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