Tutorial

New and Improved Amazon SageMaker Studio

Guide Version: 1.0 Table of Contents¶ Introduction Choosing the Right IDE Improved IDEs in SageMaker Studio Code Editor – Powered by Code-OSS Visual Studio Code Faster and Enhanced JupyterLab RStudio Integration Accelerating ML Development Data Exploration and Model Tuning with JupyterLab Deploying and Monitoring Models with Code Editor and Pipelines Full Screen Experience Simplified Training …

New and Improved Amazon SageMaker Studio Read More »

Amazon SageMaker Distribution: A Comprehensive Guide

Introduction¶ Amazon SageMaker Distribution is a powerful tool that provides Machine Learning (ML) practitioners with the flexibility to develop their ML models on the Integrated Development Environments (IDEs) of their choice. With the latest update, SageMaker Distribution is now available on Code Editor, which is based on Code-OSS and JupyterLab. This guide will explore the …

Amazon SageMaker Distribution: A Comprehensive Guide Read More »

Bring your own Amazon EFS (Elastic File System) volume to JupyterLab and CodeEditor in Amazon SageMaker Studio

Abstract In this guide, we will explore how to bring your own Amazon EFS (Elastic File System) volume to JupyterLab and CodeEditor in Amazon SageMaker Studio. We will understand the benefits of using EFS volumes and how they can enhance collaboration and productivity in ML workflows. Additionally, we will explore various technical aspects, best practices, …

Bring your own Amazon EFS (Elastic File System) volume to JupyterLab and CodeEditor in Amazon SageMaker Studio Read More »

AWS Announces Vector Search for Amazon DocumentDB

Amazon DocumentDB, the popular managed database service compatible with MongoDB, has just introduced a groundbreaking new feature: vector search. This powerful capability allows users to efficiently store, index, and search millions of vectors with incredibly fast response times in the order of milliseconds. Vectors, in this context, are numerical representations of unstructured data, such as …

AWS Announces Vector Search for Amazon DocumentDB Read More »

Observe your applications with Amazon CloudWatch Application Signals

Overview¶ Amazon CloudWatch Application Signals is a powerful new capability that simplifies the process of instrumenting and operating applications on AWS. Utilizing best practices gained from operating thousands of applications at Amazon, CloudWatch Application Signals automatically tracks application performance against your key business objectives. This eliminates the need for manual instrumentations, metric computations, and the …

Observe your applications with Amazon CloudWatch Application Signals Read More »

Title: The Ultimate Guide to Managing Applications on AWS with myApplications

Introduction¶ In the fast-paced world of cloud computing, managing applications efficiently is crucial for businesses seeking seamless operations and high performance. To address this need, AWS has introduced myApplications, a revolutionary new experience within the AWS Management Console. With myApplications, users can effortlessly view, manage, and monitor the performance, cost, security, and health of their …

Title: The Ultimate Guide to Managing Applications on AWS with myApplications Read More »

Leveraging FMs for Business Analysis at Scale with Amazon SageMaker Canvas

Introduction¶ In the world of business analysis, it is crucial to have tools and platforms that can provide accurate and insightful information to make informed decisions. Amazon SageMaker Canvas is a powerful solution that allows users to leverage Factorization Machines (FMs) for data analysis at scale. FMs are a class of machine learning models that …

Leveraging FMs for Business Analysis at Scale with Amazon SageMaker Canvas Read More »

Amazon SageMaker Pipelines: A Simplified Developer Experience for AI/ML Workflows

Introduction¶ The field of machine learning (ML) and artificial intelligence (AI) has rapidly evolved in recent years, enabling businesses to make data-driven decisions and gain valuable insights. However, ML development can be a complex and time-consuming process, often involving monolithic Python code for experimentation in a local development environment such as Jupyter notebooks. To streamline …

Amazon SageMaker Pipelines: A Simplified Developer Experience for AI/ML Workflows Read More »

Amazon EKS Ready Specialization: A Comprehensive Guide

Introduction¶ In today’s rapidly-evolving technology landscape, containerization has emerged as a game-changer for computing infrastructure. With the rise of Docker and Kubernetes, companies now have the ability to deploy and manage containerized applications rapidly, ensuring improved portability, scalability, and operational resilience. And with Amazon Web Services (AWS) leading the cloud computing market, the integration of …

Amazon EKS Ready Specialization: A Comprehensive Guide Read More »