filmov
tv
Deploying machine learning models for inference- AWS Virtual Workshop
Показать описание
Maximizing inference performance while reducing cost is critical to delivering great customer experiences through ML. Amazon SageMaker provides a breadth and depth of fully managed deployment features to achieve optimal inference performance and cost at scale without the operational burden. In this episode, learn how to use SageMaker inference capabilities to quickly deploy ML models in production for any use case, including hyper-personalization, Generative AI, and Large Language Models (LLMs).
Learning Objectives:
* Objective 1: Learn about how to deploy ML models on Amazon SageMaker for inference.
* Objective 2: Discover the SageMaker inference endpoint options that fit your use case.
* Objective 3: Learn how to deploy Large Language Models (LLMs) for inference.
Follow Amazon Web Services:
☁️ AWS Online Tech Talks cover a wide range of topics and expertise levels through technical deep dives, demos, customer examples, and live Q&A with AWS experts. Builders can choose from bite-sized 15-minute sessions, insightful fireside chats, immersive virtual workshops, interactive office hours, or watch on-demand tech talks at your own pace. Join us to fuel your learning journey with AWS.
#AWS
Learning Objectives:
* Objective 1: Learn about how to deploy ML models on Amazon SageMaker for inference.
* Objective 2: Discover the SageMaker inference endpoint options that fit your use case.
* Objective 3: Learn how to deploy Large Language Models (LLMs) for inference.
Follow Amazon Web Services:
☁️ AWS Online Tech Talks cover a wide range of topics and expertise levels through technical deep dives, demos, customer examples, and live Q&A with AWS experts. Builders can choose from bite-sized 15-minute sessions, insightful fireside chats, immersive virtual workshops, interactive office hours, or watch on-demand tech talks at your own pace. Join us to fuel your learning journey with AWS.
#AWS
0:13:12
How to Deploy Machine Learning Models (ft. Runway)
0:22:21
Deploying Machine Learning Models - Full Guide
0:04:56
Data Science 101: Deploying your Machine Learning Model
0:10:42
Deploy ML model quickly and easily | Deploying machine learning models quickly and easily
0:18:45
Deploy ML models with FastAPI, Docker, and Heroku | Tutorial
0:03:45
Machine Learning Model Deployment Explained | All About ML Model Deployment
0:14:52
Deploy Machine Learning Models using Flask
0:14:27
Deploying ML Models in Production: An Overview
0:31:46
🔵 Serving Fine-Tuned Models in Production
0:13:20
Deploy Machine Learning Model using Flask
0:11:05
Tutorial 7: Deploying Machine Learning Models In Azure Cloud
1:59:32
How to Deploy a Machine Learning Model to Google Cloud for 20% Software Engineers (CS329s tutorial)
0:12:56
Deploy Machine Learning Models Using StreamLit Library- Data Science
0:02:12
Build and Deploy a Machine Learning App in 2 Minutes
0:15:17
Tutorial 6 :Deployment of Machine Learning Models in Google Cloud Platform
0:18:58
How To Deploy Machine Learning Models Using FastAPI-Deployment Of ML Models As API’s
0:20:04
Building a Machine Learning API in 15 Minutes | Coding Challenge
0:20:26
Tutorial 4- Deployment Of ML Models In AWS EC2 Instance
0:11:39
Deployment of Machine Learning Model|How to deploy a machine learning model using flask
0:29:00
Deploy Machine Learning Model Flask
0:26:01
Five Steps for Deploying Machine Learning Models Into Production
0:40:24
Deploy Machine Learning Model using Streamlit in Python | ML model Deployment
0:29:17
Deploying Machine Learning Models Online with Watson Machine Learning | Python Scikit-Learn
0:14:50
Model deployment and inferencing with Azure Machine Learning | Machine Learning Essentials
Комментарии