ODSC - Open Data Science

JANUARY 29, 2024

Spacy: Another firm favorite, Spacy can be used for tokenization, part-of-speech tagging, and named entity recognition, aiding in structuring prompts accurately. Kubernetes: A long-established tool for containerized apps. However, users do note a steep learning curve and performance and scalability issues.

Machine Learning 52

Machine Learning Machine Learning Data Science Natural Language Processing 52

Towards AI

AUGUST 17, 2023

Image Tag and Digest Replication: Replicating image tags and digests between ECR registries is critical for security, and traceability. Alternatively, AWS recommends event-based design to selectively replicate images based on tag naming conventions. ArgoCD runs the job before the synchronizing changes.

AWS 96

AWS Clustering AI AI 96

DagsHub

AUGUST 19, 2023

Also, this model can be registered and deployed through Docker, Kubernetes, or AWS. MLflow can create a Python package that includes the model artifacts, dependencies, and config required to run your LLM when we log the model.

AWS 52

AWS Machine Learning Machine Learning Data Science 52

Snorkel AI

MARCH 30, 2023

Sequence tagging experience upgrade. NER made easy with sequence tagging We’ve made significant performance improvements (up to 20x faster) for data-centric exploration and labeling when working with sequence tagging tasks. Programmatic labeling with support for complex tasks and data types. PDF extraction improvements.

ML 98

ML ML Supervised Learning Azure 98

IBM Journey to AI blog

NOVEMBER 29, 2023

In this project, we used a loan origination application that was modernized to use Kubernetes and microservices. For each Git commit, a container image is created, and a tag is assigned to the image based on the build number, timestamp and commit ID. This tagging system ensures the image’s traceability. initiative.

Clustering 98

Clustering 98

phData

OCTOBER 2, 2023

Feast can run natively on Google Cloud Platform (GCP), or on Kubernetes in AWS. As a managed solution on top of Feast, Tecton comes with a higher price tag but will be easier for organizations to adopt and leverage. Future releases aim to bring enhanced support for AWS.

Data Warehouse 98

Data Warehouse ML ML Data Scientist 98

AWS Machine Learning Blog

APRIL 17, 2024

This post walks you through the Open Source Observability pattern for AWS Inferentia , which shows you how to monitor the performance of ML chips, used in an Amazon Elastic Kubernetes Service (Amazon EKS) cluster, with data plane nodes based on Amazon Elastic Compute Cloud (Amazon EC2) instances of type Inf1 and Inf2.

AWS 96

AWS Clustering ML ML 96

AWS Machine Learning Blog

NOVEMBER 30, 2023

Provider a cluster name and optionally any tags to apply to cluster resources, then choose Next. Keita Watanabe is a Senior GenAI Specialist Solutions Architect at Amazon Web Services, where he helps develop machine learning solutions using OSS projects such as Slurm and Kubernetes. Choose Create a cluster.

Clustering 110

Clustering AWS Machine Learning Machine Learning 110

AWS Machine Learning Blog

MAY 30, 2023

It allows you to filter and group by values such as AWS service, usage type, cost allocation tags, EC2 instance type, and more. Tagging A tag is a label that you assign to an AWS resource. You can use tags to organize your resources by users, departments, or cost centers, and track your costs on a detailed level.

AWS 64

AWS ML ML Machine Learning 64

IBM Journey to AI blog

SEPTEMBER 20, 2023

This edge cluster was also connected to an instance of Red Hat Advanced Cluster Management for Kubernetes (RHACM) hub running in the cloud.

Clustering 89

Clustering AI AI Data Science 89

Machine Learning World

MARCH 13, 2019

Docker Swarm not only orchestration engine that exist, there are also Kubernets, AWS ECS, Azure Container Service, Google Container Engine, and else. For big production application i recommend to use Kubernets. In out first case we use python image with tag 3.7.2-alpine3.9. RUN  — running a command.

AWS 52

AWS Python Azure Machine Learning 52

Flipboard

FEBRUARY 16, 2023

Solution overview AWS offers a wide variety of services for distributed model training or inferencing workloads at scale, including AWS Batch , Amazon Elastic Kubernetes Service (Amazon EKS), and UltraClusters. In this post, we use some HPC tools like Slurm to ramp an UltraCluster and manage workloads.

Clustering 106

Clustering AWS Deep Learning Deep Learning 106

The MLOps Blog

OCTOBER 3, 2023

For example, at FeatureForm, we do this because we are Kubernetes native. It can be a cluster run by Kubernetes or maybe something else. Underneath that, you might also have Kubernetes, right? Below that would be Kubernetes and Ray. I would need to have the infrastructure to perform computations.

ML 52

ML ML Data Scientist Machine Learning 52

Heartbeat

NOVEMBER 6, 2023

There are other types of executors, such as the Celery Executor, Kubernetes Executor, Dask Executor, etc. You can choose to tag the photo with any name of your choice. However, the significant difference is that the local executor allows multiple tasks to be run simultaneously. image: ${AIRFLOW_IMAGE_NAME:-apache/airflow:2.6.1}

Data Pipeline 52

Data Pipeline Clean Data ETL Python 52

The MLOps Blog

JUNE 27, 2023

Kubeflow Kubeflow is an open-source machine learning platform built for running scalable and portable ML workloads on Kubernetes. Kubeflow integrates with popular ML frameworks, supports versioning and collaboration, and simplifies the deployment and management of ML pipelines on Kubernetes clusters.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

The MLOps Blog

MARCH 21, 2023

Depending on the organization, they are either pure software engineers or simply tagged “DevOps engineers” (or IT engineers). Kubeflow Dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable, and scalable. My Story DevOps Engineers Who they are? What do they want to accomplish?

Machine Learning 69

Machine Learning Machine Learning Data Scientist ML 69

AWS Machine Learning Blog

JANUARY 9, 2023

Customers using self-managed ML solutions on Amazon Elastic Compute Cloud (Amazon EC2), Amazon Elastic Container Service (Amazon ECS), and Amazon Elastic Kubernetes Service (Amazon EKS) need to build operational tooling themselves. Customers using SageMaker incur significantly less TCO.

ML 74

ML ML AWS Deep Learning 74