- 53
- 33 095
Verta AI
United States
เข้าร่วมเมื่อ 14 มี.ค. 2020
Use Verta Model Catalog to organize, document and manage all your models in one place - easily, safely and securely.
Want to know more? Access verta.ai.
Want to know more? Access verta.ai.
Finding the best OSS model with Verta's GenAI Workbench
Learn how you can use Verta's GenAI Workbench to find the best open-source models for your application
มุมมอง: 100
วีดีโอ
Verta Demo Custom Attributes
มุมมอง 71ปีที่แล้ว
Custom attributes can empower organizations to harness the full potential of their models while promoting efficiency, governance, collaboration and long-term success. In this quick video clip, Verta's Andrea Butkovic shows how the ability to set custom attributes for models and model versions in a model catalog offers a powerful solution to the documentation challenges faced by AI/ML teams.
Verta Demo Activity Log
มุมมอง 57ปีที่แล้ว
Know every single thing about your #ML models-from versions, to how active it is, and everything in between-with a quick show and tell from our Product Manager, Andrea Butkovic. She shares why a Model Activity Log from Verta's Model Catalog (you can try it out for free btw!) will help you keep yourself and your models organized and tracked.
Share your models with your team
มุมมอง 69ปีที่แล้ว
In video show you how you can share all the benefits of Verta Platform with your team mates. Want to learn more? Sign up for free at Verta.ai
Intro to Model Catalog
มุมมอง 292ปีที่แล้ว
In this video you will learn how easy it is to register models and versions in Verta. Want to learn more about it? Sign up for free on verta.ai.
Scan for vulnerabilities and be ready for release
มุมมอง 99ปีที่แล้ว
In this video we show you how our vulnerability scan works and how can help you minimize risks during deployment of a model. Want try it? Sign up for free at verta.ai.
Verta Enterprise Model Management System
มุมมอง 366ปีที่แล้ว
Verta’s Operational AI platform supports Responsible AI, regulatory compliance, and governance and model risk management (MRM). Learn more at verta.ai
Verta: Quick Product Demo 2022
มุมมอง 5382 ปีที่แล้ว
This is a quick walkthrough of how the Verta UI supports your data science and machine learning teams on our platform. If you have any questions feel free to reach out to us at www.verta.ai/contact-us
ODSC 2022: Manasi Vartak - Why You Need a Model Catalog
มุมมอง 2282 ปีที่แล้ว
Want more on Model Catalogs? Contact andy@verta.ai
Panel Discussion: Building AI-Enabled Products
มุมมอง 762 ปีที่แล้ว
Featuring: Manasi Vartak - Founder & CEO at Verta Conrado Miranda - Co-Founder & CTO at Verta Meenakshi Sharma - Technical Product Manager at Wayfair Lukas Gubo - MLOps Project Manager at Virufy At: MLOps Salon: Building AI-Enabled Products
Automating AI development for the Edge
มุมมอง 1232 ปีที่แล้ว
Presented by: Brian Cruz, Head of Core AI at Samba TV At: MLOps Salon: Building AI-Enabled Products The ability to run Artificial Intelligence algorithms at the edge provides a number of benefits not just limited to better latency, privacy, and cost. In fact, the advent of edge computing has initiated a new paradigm for distributed computing that enables entirely new classes of products and ser...
Evolving your ML solutions with collaboration and technology
มุมมอง 532 ปีที่แล้ว
Presented by: Orestes Castaneda, Senior Business Intelligence Analyst at ViacomCBS (CBS Interactive) At: MLOps Salon: Building AI-Enabled Products As businesses and their competitive landscape evolve, more challenging business questions arise. This provides unique opportunities to develop ML applications to enable data-and-intelligence-based decision making. With that, BI and Data Science teams...
Building capabilities for ML Model Development and Training: Challenges and Best Practices
มุมมอง 1142 ปีที่แล้ว
Presented by: Meenakshi Sharma, Technical Product Manager at Wayfair At: MLOps Salon: Building AI-Enabled Products To achieve success with ML, organizations have been investing in Machine learning platforms and operations. The goal is to provide their teams, such as data scientists and engineers, to be able to perform repeatable and scalable model lifecycle management starting from exploration,...
Automation and the need of CI/CD pipeline in machine learning development
มุมมอง 912 ปีที่แล้ว
Automation and the need of CI/CD pipeline in machine learning development
How to transform experimental AI projects into successful products
มุมมอง 882 ปีที่แล้ว
How to transform experimental AI projects into successful products
Accelerating ML Workflow with Kubeflow, ModelDB, and Feast
มุมมอง 3682 ปีที่แล้ว
Accelerating ML Workflow with Kubeflow, ModelDB, and Feast
Improve ML Team Productivity w/Standardization & Automation - an Introduction to Skelebot
มุมมอง 1532 ปีที่แล้ว
Improve ML Team Productivity w/Standardization & Automation - an Introduction to Skelebot
ODSC West 2021: What is MLOps, DataOps, and DevOps
มุมมอง 3392 ปีที่แล้ว
ODSC West 2021: What is MLOps, DataOps, and DevOps
ODSC West 2021: 3 reasons why ML code is not like software
มุมมอง 732 ปีที่แล้ว
ODSC West 2021: 3 reasons why ML code is not like software
ODSC West 2021: Deliver AI & ML Models Faster, with Verta
มุมมอง 812 ปีที่แล้ว
ODSC West 2021: Deliver AI & ML Models Faster, with Verta
MLOps Salon: Applying MLOps at Scale - How to manage model lifecycle with a Model Registry
มุมมอง 883 ปีที่แล้ว
MLOps Salon: Applying MLOps at Scale - How to manage model lifecycle with a Model Registry
MLOps Salon:Applying MLOps at Scale - removing the need to write model deployment code at Stitch Fix
มุมมอง 2873 ปีที่แล้ว
MLOps Salon:Applying MLOps at Scale - removing the need to write model deployment code at Stitch Fix
MLOps Salon: Applying MLOps at Scale -Drift detection on data for monitoring ML models in production
มุมมอง 3393 ปีที่แล้ว
MLOps Salon: Applying MLOps at Scale -Drift detection on data for monitoring ML models in production
MLOps Salon: Applying MLOps at Scale - Introduction to ML Compilers
มุมมอง 753 ปีที่แล้ว
MLOps Salon: Applying MLOps at Scale - Introduction to ML Compilers
MLOps Salon: Applying MLOps at Scale - Scaling ML Platform Responsibly at DoorDash
มุมมอง 853 ปีที่แล้ว
MLOps Salon: Applying MLOps at Scale - Scaling ML Platform Responsibly at DoorDash
MLOps Salon: Applying MLOps at Scale - Algorithmic Fairness: From Theory to Practice
มุมมอง 1043 ปีที่แล้ว
MLOps Salon: Applying MLOps at Scale - Algorithmic Fairness: From Theory to Practice
MLOps Salon: Applying MLOps at Scale - Kubeflow Pipelines and Its Operational Challenges at Scale
มุมมอง 1213 ปีที่แล้ว
MLOps Salon: Applying MLOps at Scale - Kubeflow Pipelines and Its Operational Challenges at Scale