Building Multi-Modal & Agentic AI on Azure: A Step-by-Step Approach

 

Amazon (Aws) -Machine Learning Attributes

Amazon SageMaker is a powerful and user-friendly platform that can help you build and deploy machine learning models quickly and efficiently, even if you don’t have a lot of experience with machine learning or cloud computing.

Amazon SageMaker is a cloud-based platform that helps developers and data scientists build, train, and deploy machine learning models. With SageMaker, you can quickly and easily build and train machine learning models using pre-built algorithms, custom code, or vice versa.

The platform offers a wide range of tools and features to simplify the machine learning process, such as data preparation, model selection, hyperparameter tuning, and model deployment. You can also use SageMaker to scale your machine learning workloads and collaborate with other team members.

Picture Credit-https://www.xenonstack.com/blog/amazon-sagemaker-machine-learning-platform

Some Attributes which is used in mechine learning are -

1. Amazon Elastic Compute Cloud (EC2) — EC2 is a scalable cloud computing service .With EC2, you can easily launch, manage, and terminate instances as needed to meet your computing requirements.
2. Amazon Simple Storage Service (S3) — S3 is a highly scalable cloud-based object storage service. It allows you to store and retrieve any amount of data from anywhere in the world. You can use S3 for storing and backing up data, hosting static websites, and sharing files with others.
3. Amazon Redshift — Redshift is a cloud-based data warehousing solution that allows you to analyze large amounts of data using SQL queries.
4. AWS Glue — Glue is a fully managed extract, transform, and load (ETL) service that allows you to move data between different data stores and prepare the data for analysis. With Glue, you can create and manage ETL jobs to transform data at scale.
5. Amazon Comprehend — Comprehend is a natural language processing (NLP) service that allows you to analyze text data for insights such as sentiment analysis, entity recognition, and language detection. It can help you understand the meaning and context of large volumes of text data.
6. AWS Identity and Access Management (IAM)- AWS Identity and Access Management (IAM) is a web service that allows you to manage access to AWS resources securely. IAM allows you to control who can access your AWS resources (such as EC2 instances, S3 buckets, or RDS databases) and what actions they can perform on those resources.