AWS Machine Learning Blog

SEPTEMBER 11, 2024

The following figure illustrates the idea of a large cluster of GPUs being used for learning, followed by a smaller number for inference. Examples of other PBAs now available include AWS Inferentia and AWS Trainium , Google TPU, and Graphcore IPU. Suppliers of data center GPUs include NVIDIA, AMD, Intel, and others.

AWS 113

AWS ML ML Clustering 113

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.

ML 125

ML ML AWS AI 125

AWS Machine Learning Blog

NOVEMBER 3, 2023

Let’s look at some examples from the current season (2023–2024) The following videos show examples of measured shots that achieved top-speed values. 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.

AWS 127

AWS Apache Kafka Data Scientist Data Science 127

Snorkel AI

OCTOBER 9, 2024

We are proud to announce the latest generation of enterprise readiness features for Snorkel Flow introduced in our 2024.R3 In future releases, Snorkel will provide integrations with cloud-native services like AWS Secrets Manager or equivalents on GCP and Azure. Although unavailable in 2024.R3 R3 release.

Azure 52

Azure AWS Data Lakes Clustering 52

ODSC - Open Data Science

JANUARY 29, 2024

EVENT — ODSC East 2024 In-Person and Virtual Conference April 23rd to 25th, 2024 Join us for a deep dive into the latest data science and AI trends, tools, and techniques, from LLMs to data analytics and from machine learning to responsible AI.

Data Science 52

Data Science Machine Learning Machine Learning Natural Language Processing 52

DagsHub

APRIL 7, 2024

Cloud-agnostic and can run on any Kubernetes cluster. Integration: It can work alongside other workflow orchestration tools (Airflow cluster or AWS SageMaker Pipelines, etc.) The Metaflow stack can be easily deployed to any of the leading cloud providers or an on-premise Kubernetes cluster.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

DagsHub

APRIL 21, 2024

Best MLOps Tools & Platforms for 2024 In this section, you will learn about the top MLOps tools and platforms that are commonly used across organizations for managing machine learning pipelines. Data storage and versioning Some of the most popular data storage and versioning tools are Git and DVC.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

ODSC - Open Data Science

FEBRUARY 21, 2024

Thrive in the Data Tooling Tornado Adam Breindel | Independent Consultant In this talk, Adam Breindel, a leading Apache Spark instructor and authority on neural-net fraud detection, streaming analytics and cluster management code, will help you navigate the data tooling landscape. NET, and AWS.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

PyImageSearch

SEPTEMBER 30, 2024

Deployment Server Tools: Kubernetes, Docker Swarm, AWS CodeDeploy Purpose: Automates the deployment of applications to staging or production environments. Orchestration Tools: Kubernetes, Docker Swarm Purpose: Manages the deployment, scaling, and operation of application containers across clusters of hosts. What's next? Sharma, eds.,

Python 90

Python Deep Learning Deep Learning AWS 90

phData

DECEMBER 4, 2023

This blog was originally written by Erik Hyrkas and updated for 2024 by Justin Delisi This isn’t meant to be a technical how-to guide — most of those details are readily available via a quick Google search — but rather an opinionated review of key processes and potential approaches. In this case, the max cluster count should also be two.

Clustering 98

Clustering Database SQL Data Pipeline 98

Pickl AI

JUNE 7, 2024

Top contenders like Apache Airflow and AWS Glue offer unique features, empowering businesses with efficient workflows, high data quality, and informed decision-making capabilities. Also Read: Top 10 Data Science tools for 2024. Scalability: It offers scalability to handle large volumes of data across distributed computing clusters.

ETL 40

ETL Data Quality Data Pipeline Data Warehouse 40

Pickl AI

NOVEMBER 28, 2024

billion in 2024, at a CAGR of 10.7%. Key techniques in unsupervised learning include: Clustering (K-means) K-means is a clustering algorithm that groups data points into clusters based on their similarities. This growth signifies Python’s increasing role in ML and related fields. billion in 2023 to $181.15

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

NOVEMBER 4, 2024

billion by 2031, growing at a CAGR of 25.55% during the forecast period from 2024 to 2031. million in 2024 and is projected to grow at a CAGR of 26.8% billion in 2024 to USD 774.00 during the forecast period from 2024 to 2032. The global data warehouse as a service market was valued at USD 9.06 from 2025 to 2030.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

AWS Machine Learning Blog

APRIL 29, 2024

In 2024, however, organizations are using large language models (LLMs), which require relatively little focus on NLP, shifting research and development from modeling to the infrastructure needed to support LLM workflows. Historically, natural language processing (NLP) would be a primary research and development expense.

AWS 132

AWS ML ML Python 132

DagsHub

MARCH 19, 2024

Therefore, in 2024, you will very much run into apps driven by computer vision. Tesla, for instance, relies on a cluster of NVIDIA A100 GPUs to train their vision-based autonomous driving algorithms. It helped build applications around image classification, object detection, face recognition and so much more!

Algorithm 52

Algorithm Deep Learning Deep Learning Data Engineering 52

phData

OCTOBER 28, 2024

Understanding Matillion and Snowflake, the Python Component, and Why it is Used Matillion is a SaaS-based data integration platform that can be hosted in AWS, Azure, or GCP and supports multiple cloud data warehouses. This is a Custom Filewatcher using Python and AWS S3. If the file is present, it will exit successfully. 30 minutes).

Python 52

Python ETL AWS Database 52

AWS Machine Learning Blog

NOVEMBER 30, 2023

The number of companies launching generative AI applications on AWS is substantial and building quickly, including adidas, Booking.com, Bridgewater Associates, Clariant, Cox Automotive, GoDaddy, and LexisNexis Legal & Professional, to name just a few. Innovative startups like Perplexity AI are going all in on AWS for generative AI.

AWS 144

AWS AI AI ML 144

AWS Machine Learning Blog

SEPTEMBER 11, 2024

This capability allows for the seamless addition of SageMaker HyperPod managed compute to EKS clusters, using automated node and job resiliency features for foundation model (FM) development. FMs are typically trained on large-scale compute clusters with hundreds or thousands of accelerators.

Clustering 92

Clustering AWS ML ML 92

AWS Machine Learning Blog

SEPTEMBER 12, 2024

By early 2024, we are beginning to see the start of “Act 2,” in which many POCs are evolving into production, delivering significant business value. Introducing Amazon Elastic Kubernetes Service (Amazon EKS) in Amazon SageMaker HyperPod Recognizing these challenges, AWS launched Amazon SageMaker HyperPod last year.

AWS 101

AWS AI AI Clustering 101

AWS Machine Learning Blog

OCTOBER 23, 2024

SnapLogic uses Amazon Bedrock to build its platform, capitalizing on the proximity to data already stored in Amazon Web Services (AWS). To address customers’ requirements about data privacy and sovereignty, SnapLogic deploys the data plane within the customer’s VPC on AWS.

AI 90

AI AI Database AWS 90

AWS Machine Learning Blog

SEPTEMBER 19, 2024

In this post, AWS collaborates with Meta’s PyTorch team to showcase how you can use Meta’s torchtune library to fine-tune Meta Llama-like architectures while using a fully-managed environment provided by Amazon SageMaker Training. Refer to the installation instructions and PyTorch documentation to learn more about torchtune and its concepts.

AWS 100

AWS ML ML Machine Learning 100

Pickl AI

MAY 15, 2024

The Insights This comprehensive guide, updated for 2024, delves into the challenges and strategies associated with scaling Data Science careers. Embrace Distributed Processing Frameworks Frameworks like Apache Spark and Spark Streaming enable distributed processing of large datasets across clusters of machines.

Data Analyst 52

Data Analyst Data Scientist Data Science Machine Learning 52

AWS Machine Learning Blog

NOVEMBER 7, 2024

The solution was built in a recent collaboration between AWS Professional Services , under which Well-Architected machine learning design principles were followed. SageMaker Processing integrates seamlessly with AWS Identity and Access Management (IAM), Amazon Simple Storage Service (Amazon S3), AWS Step Functions , and other AWS services.

ML 120

ML ML AWS Machine Learning 120

AWS Machine Learning Blog

NOVEMBER 6, 2024

Transcribe audio with Amazon Transcribe In this case, we use an AWS re:Invent 2023 technical talk as a sample. Transcribe audio with Amazon Transcribe In this use case, we use an Amazon 2024 Q1 earnings call as a sample. Good day, everyone and welcome to the amazon.com first quarter, 2024 financial results teleconference.

AWS 123

AWS Machine Learning Machine Learning ML 123