AWS Machine Learning Blog

JULY 2, 2024

AWS optimized the PyTorch torch.compile feature for AWS Graviton3 processors. the optimizations are available in torch Python wheels and AWS Graviton PyTorch deep learning container (DLC). The goal for the AWS Graviton team was to optimize torch.compile backend for Graviton3 processors.

AWS 110

AWS Natural Language Processing Python ML 110

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 108

AWS AI AI Machine Learning 108

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. For example, you can give users access permission to download popular packages and customize the development environment.

AWS 85

AWS ML ML Data Scientist 85

Flipboard

JUNE 26, 2023

In this post, we look at how we can use AWS Glue and the AWS Lake Formation ML transform FindMatches to harmonize (deduplicate) customer data coming from different sources to get a complete customer profile to be able to provide better customer experience. Run the AWS Glue ML transform job.

AWS 123

AWS ML ML ETL 123

AWS Machine Learning Blog

OCTOBER 5, 2023

In this post, we walk through how to fine-tune Llama 2 on AWS Trainium , a purpose-built accelerator for LLM training, to reduce training times and costs. We review the fine-tuning scripts provided by the AWS Neuron SDK (using NeMo Megatron-LM), the various configurations we used, and the throughput results we saw.

AWS 115

AWS Machine Learning Machine Learning Deep Learning 115

AWS Machine Learning Blog

OCTOBER 10, 2023

Customers often need to train a model with data from different regions, organizations, or AWS accounts. Existing partner open-source FL solutions on AWS include FedML and NVIDIA FLARE. These open-source packages are deployed in the cloud by running in virtual machines, without using the cloud-native services available on AWS.

AWS 111

AWS ML ML Algorithm 111

AWS Machine Learning Blog

JUNE 23, 2023

Additionally, you can use AWS Lambda directly to expose your models and deploy your ML applications using your preferred open-source framework, which can prove to be more flexible and cost-effective. FastAPI is a modern, high-performance web framework for building APIs with Python. This will be used to deploy our solution.

AWS 94

AWS ML ML Python 94

AWS Machine Learning Blog

MAY 3, 2023

AWS, Arm, Meta and others helped optimize the performance of PyTorch 2.0 As a result, we are delighted to announce that AWS Graviton-based instance inference performance for PyTorch 2.0 times the speed for BERT, making Graviton-based instances the fastest compute optimized instances on AWS for these models. is up to 3.5

AWS 93

AWS Cloud Computing Python Machine Learning 93

DrivenData Labs

NOVEMBER 14, 2023

VIIRS' Day/Night Band (DNB) sensor captures nightlight imagery that is useful for mapping populations. ECOSTRESS has been used in the midwestern United States to detects droughts early enough to recover and protect crops.

Python 163

Python AWS Azure Data Analysis 163

AWS Machine Learning Blog

MAY 1, 2024

Llama2 by Meta is an example of an LLM offered by AWS. To learn more about Llama 2 on AWS, refer to Llama 2 foundation models from Meta are now available in Amazon SageMaker JumpStart. Virginia) and US West (Oregon) AWS Regions, and most recently announced general availability in the US East (Ohio) Region.

AWS 107

AWS ML ML Clustering 107

AWS Machine Learning Blog

MARCH 15, 2024

In addition to Amazon Bedrock, you can use other AWS services like Amazon SageMaker JumpStart and Amazon Lex to create fully automated and easily adaptable generative AI order processing agents. In this post, we show you how to build a speech-capable order processing agent using Amazon Lex, Amazon Bedrock, and AWS Lambda.

AWS 131

AWS AI AI Python 131

AWS Machine Learning Blog

MARCH 8, 2023

This post shows a way to do this using Snowflake as the data source and by downloading the data directly from Snowflake into a SageMaker Training job instance. We create a custom training container that downloads data directly from the Snowflake table into the training instance rather than first downloading the data into an S3 bucket.

ML 121

ML ML AWS Python 121

AWS Machine Learning Blog

JUNE 4, 2024

Terraform is an IaC tool that allows you to manage AWS resources, software as a service (SaaS) resources, datasets, and more, using declarative configuration. Configure your local Python virtual environment. Download the DialogSum public dataset and convert it to JSONL. python v3.8 Terraform v1.0.0 or newer installed.

AWS 126

AWS Python Artificial Intelligence Artificial Intelligence 126

AWS Machine Learning Blog

MAY 4, 2023

AWS has been innovating with purpose-built chips to address the growing need for powerful, efficient, and cost-effective compute hardware. You can use ml.trn1 and ml.inf2 compatible AWS Deep Learning Containers (DLCs) for PyTorch, TensorFlow, Hugging Face, and large model inference (LMI) to easily get started. petaflops for BF16/FP16.

AWS 83

AWS Deep Learning Deep Learning ML 83

AWS Machine Learning Blog

AUGUST 30, 2023

This post demonstrates a strategy for fine-tuning publicly available LLMs for the task of radiology report summarization using AWS services. In the following sections, we demonstrate fine-tuning an LLM available on SageMaker JumpStart for summarization of a domain-specific task via the SageMaker Python SDK. We use an ml.t3.medium

AWS 126

AWS AI AI ML 126

Flipboard

DECEMBER 11, 2024

Discover your data and put it to work using familiar AWS tools to complete end-to-end development workflows, including data analysis, data processing, model training, generative AI app building, and more, in a single governed environment. Youre redirected to the AWS CloudFormation console to deploy a stack to configure VPC resources.

SQL 156

SQL AWS Data Lakes AI 156

Flipboard

MARCH 7, 2023

This post presents and compares options and recommended practices on how to manage Python packages and virtual environments in Amazon SageMaker Studio notebooks. You can manage app images via the SageMaker console, the AWS SDK for Python (Boto3), and the AWS Command Line Interface (AWS CLI). Define a Dockerfile.

Python 123

Python AWS ML ML 123

AWS Machine Learning Blog

NOVEMBER 14, 2024

Streamlit is an open source framework for data scientists to efficiently create interactive web-based data applications in pure Python. Prerequisites To perform this solution, complete the following: Create and activate an AWS account. Make sure your AWS credentials are configured correctly. Install Python 3.7

AWS 99

AWS Python AI AI 99

Flipboard

NOVEMBER 27, 2024

In this post, we show you how to integrate the popular Slack messaging service with AWS generative AI services to build a natural language assistant where business users can ask questions of an unstructured dataset. In this solution, we have enabled the AWS provided profanity filter.

AWS 140

AWS AI AI Database 140

AWS Machine Learning Blog

SEPTEMBER 23, 2024

Prerequisties The proposed solution can be implemented in a personal AWS environment using the code that we provide. Before running the labs in this post, ensure you have the following: An AWS account. The appropriate AWS Identity and Access Management (IAM) permissions to access services used in the lab.

AWS 121

AWS Data Scientist Machine Learning Machine Learning 121

PyImageSearch

SEPTEMBER 30, 2024

Home Table of Contents Introduction to GitHub Actions for Python Projects Introduction What Is CICD? For Python projects, CI/CD pipelines ensure that your code is consistently integrated and delivered with high quality and reliability. Git is the most commonly used VCS for Python projects, enabling collaboration and version tracking.

Python 86

Python Deep Learning Deep Learning AWS 86

AWS Machine Learning Blog

AUGUST 26, 2024

AWS makes it possible for organizations of all sizes and developers of all skill levels to build and scale generative AI applications with security, privacy, and responsible AI. In this post, we dive into the architecture and implementation details of GenASL, which uses AWS generative AI capabilities to create human-like ASL avatar videos.

AWS 114

AWS AI AI ML 114

AWS Machine Learning Blog

SEPTEMBER 20, 2023

For example, you might have acquired a company that was already running on a different cloud provider, or you may have a workload that generates value from unique capabilities provided by AWS. We show how you can build and train an ML model in AWS and deploy the model in another platform.

ML 115

ML ML Azure AWS 115

AWS Machine Learning Blog

APRIL 7, 2023

To reduce the barrier to entry of ML at the edge, we wanted to demonstrate an example of deploying a pre-trained model from Amazon SageMaker to AWS Wavelength , all in less than 100 lines of code. In this post, we demonstrate how to deploy a SageMaker model to AWS Wavelength to reduce model inference latency for 5G network-based applications.

AWS 87

AWS Clustering ML ML 87

Flipboard

NOVEMBER 20, 2023

We use two AWS Media & Entertainment Blog posts as the sample external data, which we convert into embeddings with the BAAI/bge-small-en-v1.5 Prerequisites To follow the steps in this post, you need to have an AWS account and an AWS Identity and Access Management (IAM) role with permissions to create and access the solution resources.

AWS 165

AWS Database Machine Learning Machine Learning 165

AWS Machine Learning Blog

MAY 9, 2023

In this post, we help you understand the Python backend that is supported by Triton on SageMaker so that you can make an informed decision for your workloads and achieve great results. Triton supports instance types that support GPUs, CPUs, and AWS Inferentia chips, which allow you to maximize the performance for your workloads.

Python 94

Python ML ML Deep Learning 94

AWS Machine Learning Blog

JUNE 6, 2023

PyTorch is a machine learning (ML) framework that is widely used by AWS customers for a variety of applications, such as computer vision, natural language processing, content creation, and more. release, AWS customers can now do same things as they could with PyTorch 1.x 24xlarge with AWS PyTorch 2.0 on AWS PyTorch2.0

AWS 72

AWS ML ML Deep Learning 72

AWS Machine Learning Blog

FEBRUARY 20, 2024

With an aim to accelerate the localization of content workflows through machine learning, ZOO Digital engaged AWS Prototyping, an investment program by AWS to co-build workloads with customers. This S3 bucket was configured to emit an event when new files are detected within it, triggering an AWS Lambda function.

AWS 112

AWS AI AI Machine Learning 112

AWS Machine Learning Blog

JULY 26, 2023

In this post, we show how you can run Stable Diffusion models and achieve high performance at the lowest cost in Amazon Elastic Compute Cloud (Amazon EC2) using Amazon EC2 Inf2 instances powered by AWS Inferentia2. versions on AWS Inferentia2 cost-effectively. You can run both Stable Diffusion 2.1 The Stable Diffusion 2.1

AWS 83

AWS Deep Learning Deep Learning ML 83

AWS Machine Learning Blog

JULY 2, 2024

AWS Amplify to create and deploy the web application. Amazon API Gateway and AWS Lambda to create an API with an authentication layer and integrate with Amazon Bedrock. The AWS Well-Architected Framework documentation. The Implementing Microservices on AWS whitepaper. Refer to the Amazon Bedrock FAQs for further details.

AWS 119

AWS Artificial Intelligence Artificial Intelligence Database 119

AWS Machine Learning Blog

APRIL 25, 2024

We provide a comprehensive guide on how to deploy speaker segmentation and clustering solutions using SageMaker on the AWS Cloud. Solution overview Amazon Transcribe is the go-to service for speaker diarization in AWS. PyAnnote is an open source toolkit written in Python for speaker diarization.

AWS 113

AWS ML ML Python 113

AWS Machine Learning Blog

MAY 31, 2023

You can submit a document from the AWS Management Console , AWS Command Line Interface (AWS CLI), or AWS SDK and receive the translated document in real time while maintaining the format of the original document. The translated file is automatically saved to your browser’s downloaded folder, usually to Downloads.

AWS 88

AWS Natural Language Processing Python ML 88

The MLOps Blog

MAY 10, 2023

How to save a trained model in Python? Saving trained model with pickle The pickle module can be used to serialize and deserialize the Python objects. For saving the ML models used as a pickle file, you need to use the Pickle module that already comes with the default Python installation. Now let’s see how we can save our model.

Python 105

Python ML ML Database 105

AWS Machine Learning Blog

DECEMBER 12, 2023

The launch of ChatGPT and rise in popularity of generative AI have captured the imagination of customers who are curious about how they can use this technology to create new products and services on AWS, such as enterprise chatbots, which are more conversational. Optionally, deploy the application using AWS Amplify.

AWS 116

AWS ML ML AI 116

AWS Machine Learning Blog

OCTOBER 19, 2023

Additionally, using Amazon Comprehend with AWS PrivateLink means that customer data never leaves the AWS network and is continuously secured with the same data access and privacy controls as the rest of your applications. Download the SageMaker Data Wrangler flow. Review the SageMaker Data Wrangler flow. Add a destination node.

Machine Learning 105

Machine Learning Machine Learning ML ML 105

AWS Machine Learning Blog

APRIL 16, 2024

Jupyter notebooks can differentiate between SQL and Python code using the %%sm_sql magic command, which must be placed at the top of any cell that contains SQL code. This command signals to JupyterLab that the following instructions are SQL commands rather than Python code. or later image versions. or later image versions.

SQL 106

SQL AWS Database Data Scientist 106

AWS Machine Learning Blog

FEBRUARY 19, 2024

git clone --depth 2 --filter=blob:none --no-checkout [link] && cd amazon-bedrock-samples && git checkout main rag-solutions/contextual-chatbot-using-knowledgebase Upload your knowledge dataset to Amazon S3 We download the dataset for our knowledge base and upload it into a S3 bucket. Note this is one single git clone command.

AWS 108

AWS Database Machine Learning Machine Learning 108