Скачать или смотреть SageMaker Jumpstart: 6 Things You HAVE To Know (AWS) 😇

Amazon SageMaker JumpStart provides a set of prebuilt machine-learning solutions for the most common use cases that can be readily deployed with just a few clicks.

Hi Guys, this is Abi from GokceDB and in this video, you are going to learn 6 things about SageMaker Jumpstart in AWS. Let's get into it.

1. SageMaker JumpStart provides foundation models and supports one-click deployment and fine-tuning of more than 150 popular open-source models such as transformer, object detection, and image classification.

2. The machine learning solutions are fully customizable and feature the use of AWS CloudFormation templates and reference architectures so you can accelerate your machine learning lifecycle.

3. SageMaker gives you ownership and control over your content through simple yet powerful tools. It allows you to determine where your content will be stored and secure your content in both transit and at rest. You can also manage your access to AWS services and resources for your users.

4. With SageMaker JumpStart, data scientists and developers can easily share machine learning artifacts such as notebooks and models, within their organization.

5. SageMaker JumpStart does not use customer models, training data, or algorithms to improve its own service and does not share customer training and inference data with third parties. Since all data is encrypted and does not leave your VPC, you can trust that your data will remain confidential.

6. The service allows you to try out both public and proprietary foundation models and easily customize and integrate them in your generative AI applications.

In summary, Amazon SageMaker JumpStart provides hundreds of built-in algorithms with pre-trained models that cover common machine learning tasks, such as data classifications, media generation, and sentiment analysis.

There you have it.