AWS and Python - Data Science Current

Using AWS S3 with Python boto3

Analytics Vidhya

DECEMBER 5, 2022

Source: [link] Introduction AWS S3 is one of the object storage services offered by Amazon Web Services or AWS. The post Using AWS S3 with Python boto3 appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon.

AWS

AWS Python Data Science Analytics

Build and deploy a UI for your generative AI applications with AWS and Python

AWS Machine Learning Blog

NOVEMBER 6, 2024

AWS provides a powerful set of tools and services that simplify the process of building and deploying generative AI applications, even for those with limited experience in frontend and backend development. The Python application uses the Streamlit library to provide a user-friendly interface for interacting with a generative AI model.

AWS

AWS Python AI AI

Build generative AI applications on Amazon Bedrock with the AWS SDK for Python (Boto3)

AWS Machine Learning Blog

NOVEMBER 22, 2024

Because Amazon Bedrock is serverless, you don’t have to manage any infrastructure, and you can securely integrate and deploy generative AI capabilities into your applications using the AWS services you are already familiar with. client( service_name="bedrock-runtime", region_name="us-east-1" ) Define the model to invoke using its model ID.

AWS

AWS Python AI AI

Webinars

What’s New in Apache Airflow® 3.0—And How Will It Reshape Your Data Workflows?

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Don’t Manage Your Python Environments, Just Use Docker Containers

KDnuggets

JANUARY 28, 2025

Python environment management can sometimes give you that awful feeling in the pit of your stomach. So don't do it: just use Docker containers.

Python

Python AWS

A primer on AWS Lambda Function

Analytics Vidhya

AUGUST 25, 2022

AWS Lambda is a service that allows developers to run code without having to set up and manage such servers and hence is often classified under the […]. The post A primer on AWS Lambda Function appeared first on Analytics Vidhya.

AWS

AWS Data Science Analytics Analytics

Deploying a Flask App on AWS Elastic Beanstalk

Analytics Vidhya

NOVEMBER 1, 2021

Image 1- [link] Whether you are an experienced or an aspiring data scientist, you must have worked on machine learning model development comprising of data cleaning, wrangling, comparing different ML models, training the models on Python Notebooks like Jupyter. All the […].

AWS

AWS Data Scientist Machine Learning Machine Learning

AWS Elastic Beanstalk and AWS Lambda: A Practical Guide & CCP Exam

Analytics Vidhya

FEBRUARY 1, 2024

AWS (Amazon Web Services) is a formidable force in this landscape. Once you navigate the complexities, two services, AWS Elastic Beanstalk and AWS Lambda, often become vital concerns. The question […] The post AWS Elastic Beanstalk and AWS Lambda: A Practical Guide & CCP Exam appeared first on Analytics Vidhya.

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Creating and Managing DynamoDB Tables using AWS CLI

Analytics Vidhya

NOVEMBER 23, 2022

Source: [link] Introduction The AWS Command Line Interface (CLI) is a centralized management tool for managing AWS services. With this one tool, it can handle multiple AWS services from the […]. The post Creating and Managing DynamoDB Tables using AWS CLI appeared first on Analytics Vidhya.

AWS

AWS Data Science Analytics Analytics

Population Health Analytics with AWS HealthLake and QuickSight

Analytics Vidhya

APRIL 5, 2022

The post Population Health Analytics with AWS HealthLake and QuickSight appeared first on Analytics Vidhya. Medical Interoperability is the ability to integrate and share secure healthcare information promptly across multiple systems. Medical Interoperability along with AI & Machine Learning […].

AWS

AWS Analytics Analytics Machine Learning

How to Deploy a Machine learning model on AWS EC2

Analytics Vidhya

SEPTEMBER 16, 2022

Introduction AWS is a cloud computing service that provides on-demand computing resources for storage, networking, Machine learning, etc on a pay-as-you-go pricing model. AWS is a premier cloud computing platform around the globe, and most organization uses AWS for global networking and data […].

Machine Learning

Machine Learning Machine Learning AWS Cloud Computing

Build a Serverless News Data Pipeline using ML on AWS Cloud

KDnuggets

NOVEMBER 18, 2021

This is the guide on how to build a serverless data pipeline on AWS with a Machine Learning model deployed as a Sagemaker endpoint.

Data Pipeline

Data Pipeline AWS ML ML

Using AWS Athena and QuickSight for Data Analysis

Analytics Vidhya

AUGUST 25, 2022

The post Using AWS Athena and QuickSight for Data Analysis appeared first on Analytics Vidhya. Also, have you ever tried doing this with Athena and QuickSight? This blog post will walk you through the necessary steps to achieve this using Amazon services and tools. Amazon’s perfect combination of […].

Data Analysis

Data Analysis Data Analysis AWS Data Science

Basic Concept and Backend of AWS Elasticsearch

Analytics Vidhya

OCTOBER 4, 2022

It is a Lucene-based search engine developed in Java but supports clients in various languages such as Python, C#, Ruby, and PHP. The post Basic Concept and Backend of AWS Elasticsearch appeared first on Analytics Vidhya. It takes unstructured data from multiple sources as input and stores it […].

AWS

AWS Data Science Python Analytics

Building ML Model in AWS Sagemaker

Analytics Vidhya

FEBRUARY 21, 2022

The post Building ML Model in AWS Sagemaker appeared first on Analytics Vidhya. AI/ML has become an integral part of research and innovations. The main objective of the AI system is to solve real-world problems where […].

AWS

AWS ML ML Artificial Intelligence

Your guide to generative AI and ML at AWS re:Invent 2024

AWS Machine Learning Blog

NOVEMBER 19, 2024

The excitement is building for the fourteenth edition of AWS re:Invent, and as always, Las Vegas is set to host this spectacular event. Third, we’ll explore the robust infrastructure services from AWS powering AI innovation, featuring Amazon SageMaker , AWS Trainium , and AWS Inferentia under AI/ML, as well as Compute topics.

AWS

AWS ML ML AI

Racing into the future: How AWS DeepRacer fueled my AI and ML journey

AWS Machine Learning Blog

NOVEMBER 19, 2024

In 2018, I sat in the audience at AWS re:Invent as Andy Jassy announced AWS DeepRacer —a fully autonomous 1/18th scale race car driven by reinforcement learning. But AWS DeepRacer instantly captured my interest with its promise that even inexperienced developers could get involved in AI and ML.

AWS

AWS ML ML AI

Evaluate large language models for your machine translation tasks on AWS

AWS Machine Learning Blog

JANUARY 7, 2025

The translation playground could be adapted into a scalable serverless solution as represented by the following diagram using AWS Lambda , Amazon Simple Storage Service (Amazon S3), and Amazon API Gateway. To run the project code, make sure that you have fulfilled the AWS CDK prerequisites for Python.

AWS

AWS Python AI AI

AWS Lambda: A Convenient Way to Send Emails and Analyze Logs

Analytics Vidhya

JANUARY 1, 2023

convenient Introduction AWS Lambda is a serverless computing service that lets you run code in response to events while having the underlying compute resources managed for you automatically. The post AWS Lambda: A Convenient Way to Send Emails and Analyze Logs appeared first on Analytics Vidhya.

AWS

AWS Data Science Analytics Analytics

Introduction to Amazon API Gateway using AWS Lambda

Analytics Vidhya

JANUARY 1, 2023

The post Introduction to Amazon API Gateway using AWS Lambda appeared first on Analytics Vidhya. If you want to make noodles, you just take the ingredients out of the cupboard, fire up the stove, and make it yourself. This […].

AWS

AWS Analytics Analytics Data Engineer

What Are the Best Practices for Deploying PySpark on AWS?

Analytics Vidhya

NOVEMBER 7, 2023

Deploying PySpark on AWS applications on the cloud can be a game-changer, offering scalability and flexibility for data-intensive tasks. Amazon Web Services (AWS) provides an ideal platform for such deployments, and when combined […] The post What Are the Best Practices for Deploying PySpark on AWS?

AWS

AWS Big Data Big Data Analytics

Streamlining Data Workflow with Apache Airflow on AWS EC2

Analytics Vidhya

APRIL 23, 2024

This article explores the intricacies of automating ETL pipelines using Apache Airflow on AWS EC2. It […] The post Streamlining Data Workflow with Apache Airflow on AWS EC2 appeared first on Analytics Vidhya.

AWS

AWS ETL Data Pipeline Analytics

PEFT fine tuning of Llama 3 on SageMaker HyperPod with AWS Trainium

AWS Machine Learning Blog

DECEMBER 24, 2024

To simplify infrastructure setup and accelerate distributed training, AWS introduced Amazon SageMaker HyperPod in late 2023. In this blog post, we showcase how you can perform efficient supervised fine tuning for a Meta Llama 3 model using PEFT on AWS Trainium with SageMaker HyperPod. architectures/5.sagemaker-hyperpod/LifecycleScripts/base-config/

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AWS Clustering Deep Learning Deep Learning

Generate AWS Resilience Hub findings in natural language using Amazon Bedrock

AWS Machine Learning Blog

NOVEMBER 18, 2024

In this post, we explore how to use the power of AWS Resilience Hub and Amazon Bedrock to bridge this gap and streamline the process of sharing architectural findings across your organization. Prerequisites For this walkthrough, the following are required: An AWS account. AWS Management Console access. A Python 3.12

AWS

AWS AI AI Machine Learning

Working with DynamoDb in Python using BOTO3

Analytics Vidhya

MAY 20, 2022

Source: Link Introduction In this article, we are going to talk about a dynamo DB a No-SQL, and a very highly scalable database provided by Amazon AWS. The post Working with DynamoDb in Python using BOTO3 appeared first on Analytics Vidhya. It is […].

Python

Python Database AWS SQL

Run small language models cost-efficiently with AWS Graviton and Amazon SageMaker AI

Flipboard

JUNE 5, 2025

AWS has always provided customers with choice. In terms of hardware choice, in addition to NVIDIA GPUs and AWS custom AI chips, CPU-based instances represent (thanks to the latest innovations in CPU hardware) an additional choice for customers who want to run generative AI inference, like hosting small language models and asynchronous agents.

AWS

AWS AI AI ML

Automate Model Deployment with GitHub Actions and AWS

Analytics Vidhya

SEPTEMBER 28, 2022

The post Automate Model Deployment with GitHub Actions and AWS appeared first on Analytics Vidhya. First, you build software, test it for possible faults, and finally deploy it for the end user’s accessibility. The same can be applied to […].

AWS

AWS Data Science Analytics Analytics

Deploy Meta Llama 3.1 models cost-effectively in Amazon SageMaker JumpStart with AWS Inferentia and AWS Trainium

AWS Machine Learning Blog

NOVEMBER 25, 2024

8B and 70B inference support on AWS Trainium and AWS Inferentia instances in Amazon SageMaker JumpStart. Trainium and Inferentia, enabled by the AWS Neuron software development kit (SDK), offer high performance and lower the cost of deploying Meta Llama 3.1 An AWS Identity and Access Management (IAM) role to access SageMaker.

AWS

AWS Python ML ML

Apply Amazon SageMaker Studio lifecycle configurations using AWS CDK

AWS Machine Learning Blog

NOVEMBER 26, 2024

Solution overview The solution constitutes a best-practice Amazon SageMaker domain setup with a configurable list of domain user profiles and a shared SageMaker Studio space using the AWS Cloud Development Kit (AWS CDK). The AWS CDK is a framework for defining cloud infrastructure as code. The AWS CDK installed.

AWS

AWS Data Scientist ML ML

Building a Complete Web Application in AWS Services

Analytics Vidhya

JULY 14, 2023

Introduction When we start learning AWS, we usually learn bits and pieces of it, like some of the core services; working around the AWS console, we could create a new ec2 instance or an s3 bucket and upload something to it. But in most cases, we couldn’t put all the services together into an actual application.

AWS

AWS Analytics Analytics Database

Accelerating ML experimentation with enhanced security: AWS PrivateLink support for Amazon SageMaker with MLflow

AWS Machine Learning Blog

DECEMBER 9, 2024

It simplifies the often complex and time-consuming tasks involved in setting up and managing an MLflow environment, allowing ML administrators to quickly establish secure and scalable MLflow environments on AWS. AWS CodeArtifact , which provides a private PyPI repository so that SageMaker can use it to download necessary packages.

AWS

AWS ML ML Data Scientist

Building End-to-End Generative AI Models with AWS Bedrock

Analytics Vidhya

FEBRUARY 22, 2024

As we know, we are currently using the VIT […] The post Building End-to-End Generative AI Models with AWS Bedrock appeared first on Analytics Vidhya. The evaluation of Gen AI began with the Transformer architecture, and this strategy has since been adopted in other fields. Let’s take an example.

AWS

AWS AI AI Analytics

Crafting Serverless ETL Pipeline Using AWS Glue and PySpark

Analytics Vidhya

DECEMBER 26, 2022

The post Crafting Serverless ETL Pipeline Using AWS Glue and PySpark appeared first on Analytics Vidhya. It involves extracting the operational data from various sources, transforming it into a format suitable for business needs, and loading it into data storage systems. Traditionally, ETL processes are […].

ETL

ETL AWS Data Engineering Data Engineering

What is AWS EMR? Here’s Everything you Need to Know

Analytics Vidhya

MARCH 4, 2024

Enter AWS EMR, or Amazon Elastic […] The post What is AWS EMR? This question has plagued many businesses and organizations as they navigate the complexities of big data. From log analysis to financial modeling, the need for scalable and flexible solutions has never been greater.

AWS

AWS Big Data Big Data Analytics

Introducing AWS MCP Servers for code assistants (Part 1)

AWS Machine Learning Blog

APRIL 1, 2025

Were excited to announce the open source release of AWS MCP Servers for code assistants a suite of specialized Model Context Protocol (MCP) servers that bring Amazon Web Services (AWS) best practices directly to your development workflow. This post is the first in a series covering AWS MCP Servers.

AWS

AWS AI AI Python

Introducing SageMaker Core: A new object-oriented Python SDK for Amazon SageMaker

AWS Machine Learning Blog

OCTOBER 15, 2024

We’re excited to announce the release of SageMaker Core , a new Python SDK from Amazon SageMaker designed to offer an object-oriented approach for managing the machine learning (ML) lifecycle. The SageMaker Core SDK comes bundled as part of the SageMaker Python SDK version 2.231.0 or greater is installed in the environment.

Python

Python AWS ML ML

How Crexi achieved ML models deployment on AWS at scale and boosted efficiency

AWS Machine Learning Blog

NOVEMBER 26, 2024

Solutions should be flexible to adopt, allow seamless integration with other systems, and provide a path to automate MLOps using AWS services and third-party tools, as we’ll explore in this post with Pulumi and Datadog. Lastly, the model-c endpoint also has access to input S3 objects in the Crexi AWS account in addition to Amazon Textract.

AWS

AWS ML ML Data Scientist

Building a Data Pipeline with PySpark and AWS

Analytics Vidhya

AUGUST 3, 2021

The post Building a Data Pipeline with PySpark and AWS appeared first on Analytics Vidhya. ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Apache Spark is a framework used in cluster computing environments.

Data Pipeline

Data Pipeline AWS Clustering Data Science

Align and monitor your Amazon Bedrock powered insurance assistance chatbot to responsible AI principles with AWS Audit Manager

AWS Machine Learning Blog

JANUARY 7, 2025

To address this need, AWS generative AI best practices framework was launched within AWS Audit Manager , enabling auditing and monitoring of generative AI applications. Figure 1 depicts the systems functionalities and AWS services. Select AWS Generative AI Best Practices Framework for assessment. Choose Create assessment.

AWS

AWS AI AI Database

Accelerate custom labeling workflows in Amazon SageMaker Ground Truth without using AWS Lambda

AWS Machine Learning Blog

OCTOBER 31, 2024

Previously, setting up a custom labeling job required specifying two AWS Lambda functions: a pre-annotation function, which is run on each dataset object before it’s sent to workers, and a post-annotation function, which is run on the annotations of each dataset object and consolidates multiple worker annotations if needed.

AWS

AWS Natural Language Processing ML ML

Creating an ML Web App and Deploying it on AWS

Analytics Vidhya

MAY 20, 2022

The post Creating an ML Web App and Deploying it on AWS appeared first on Analytics Vidhya. Some modern applications deploy embedded models in edge and mobile devices. ML web app Model creation is easy but the ML model that you […].

ML

ML ML AWS Data Science

AWS DeepRacer: How to master physical racing?

AWS Machine Learning Blog

DECEMBER 1, 2024

In this blog post, I will look at what makes physical AWS DeepRacer racing—a real car on a real track—different to racing in the virtual world—a model in a simulated 3D environment. The AWS DeepRacer League is wrapping up. The original AWS DeepRacer, without modifications, has a smaller speed range of about 2 meters per second.

AWS

AWS Python Artificial Intelligence Artificial Intelligence

HCLTech’s AWS powered AutoWise Companion: A seamless experience for informed automotive buyer decisions with data-driven design

AWS Machine Learning Blog

JANUARY 15, 2025

Powered by generative AI services on AWS and large language models (LLMs) multi-modal capabilities, HCLTechs AutoWise Companion provides a seamless and impactful experience. Technical architecture The overall solution is implemented using AWS services and LangChain. AWS Glue AWS Glue is used for data cataloging.

AWS

AWS SQL AI AI

Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning Blog

OCTOBER 31, 2024

AWS offers powerful generative AI services , including Amazon Bedrock , which allows organizations to create tailored use cases such as AI chat-based assistants that give answers based on knowledge contained in the customers’ documents, and much more. The following figure illustrates the high-level design of the solution.

AWS

AWS AI AI Python

Serving LLMs using vLLM and Amazon EC2 instances with AWS AI chips

AWS Machine Learning Blog

NOVEMBER 26, 2024

Using vLLM on AWS Trainium and Inferentia makes it possible to host LLMs for high performance inference and scalability. Deploy vLLM on AWS Trainium and Inferentia EC2 instances In these sections, you will be guided through using vLLM on an AWS Inferentia EC2 instance to deploy Meta’s newest Llama 3.2 You will use inf2.xlarge

AWS

AWS AI AI Artificial Intelligence

Using AWS S3 with Python boto3

Build and deploy a UI for your generative AI applications with AWS and Python

Webinars

Trending Sources

Build generative AI applications on Amazon Bedrock with the AWS SDK for Python (Boto3)

Webinars

Don’t Manage Your Python Environments, Just Use Docker Containers

A primer on AWS Lambda Function

Deploying a Flask App on AWS Elastic Beanstalk

AWS Elastic Beanstalk and AWS Lambda: A Practical Guide & CCP Exam

Creating and Managing DynamoDB Tables using AWS CLI

Population Health Analytics with AWS HealthLake and QuickSight

How to Deploy a Machine learning model on AWS EC2

Build a Serverless News Data Pipeline using ML on AWS Cloud

Using AWS Athena and QuickSight for Data Analysis

Basic Concept and Backend of AWS Elasticsearch

Building ML Model in AWS Sagemaker

Your guide to generative AI and ML at AWS re:Invent 2024

Racing into the future: How AWS DeepRacer fueled my AI and ML journey

Evaluate large language models for your machine translation tasks on AWS

AWS Lambda: A Convenient Way to Send Emails and Analyze Logs

Introduction to Amazon API Gateway using AWS Lambda

What Are the Best Practices for Deploying PySpark on AWS?

Streamlining Data Workflow with Apache Airflow on AWS EC2

PEFT fine tuning of Llama 3 on SageMaker HyperPod with AWS Trainium

Generate AWS Resilience Hub findings in natural language using Amazon Bedrock

Working with DynamoDb in Python using BOTO3

Run small language models cost-efficiently with AWS Graviton and Amazon SageMaker AI

Automate Model Deployment with GitHub Actions and AWS

Deploy Meta Llama 3.1 models cost-effectively in Amazon SageMaker JumpStart with AWS Inferentia and AWS Trainium

Apply Amazon SageMaker Studio lifecycle configurations using AWS CDK

Building a Complete Web Application in AWS Services

Accelerating ML experimentation with enhanced security: AWS PrivateLink support for Amazon SageMaker with MLflow

Building End-to-End Generative AI Models with AWS Bedrock

Crafting Serverless ETL Pipeline Using AWS Glue and PySpark

What is AWS EMR? Here’s Everything you Need to Know

Introducing AWS MCP Servers for code assistants (Part 1)

Introducing SageMaker Core: A new object-oriented Python SDK for Amazon SageMaker

How Crexi achieved ML models deployment on AWS at scale and boosted efficiency

Building a Data Pipeline with PySpark and AWS

Align and monitor your Amazon Bedrock powered insurance assistance chatbot to responsible AI principles with AWS Audit Manager

Accelerate custom labeling workflows in Amazon SageMaker Ground Truth without using AWS Lambda

Creating an ML Web App and Deploying it on AWS

AWS DeepRacer: How to master physical racing?

HCLTech’s AWS powered AutoWise Companion: A seamless experience for informed automotive buyer decisions with data-driven design

Create a generative AI–powered custom Google Chat application using Amazon Bedrock

Serving LLMs using vLLM and Amazon EC2 instances with AWS AI chips

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