AWS Machine Learning Blog

APRIL 7, 2025

Virginia) AWS Region. Prerequisites To try the Llama 4 models in SageMaker JumpStart, you need the following prerequisites: An AWS account that will contain all your AWS resources. An AWS Identity and Access Management (IAM) role to access SageMaker AI. Access to accelerated instances (GPUs) for hosting the LLMs.

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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.

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AWS Machine Learning Blog

SEPTEMBER 18, 2024

As an early adopter of large language model (LLM) technology, Zeta released Email Subject Line Generation in 2021. In addition to its groundbreaking AI innovations, Zeta Global has harnessed Amazon Elastic Container Service (Amazon ECS) with AWS Fargate to deploy a multitude of smaller models efficiently.

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AWS Machine Learning Blog

MAY 10, 2023

Given the importance of Jupyter to data scientists and ML developers, AWS is an active sponsor and contributor to Project Jupyter. In parallel to these open-source contributions, we have AWS product teams who are working to integrate Jupyter with products such as Amazon SageMaker.

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AWS Machine Learning Blog

MARCH 1, 2023

In this post, we share how Kakao Games and the Amazon Machine Learning Solutions Lab teamed up to build a scalable and reliable LTV prediction solution by using AWS data and ML services such as AWS Glue and Amazon SageMaker. It was launched in June 2021 and has been ranked within the top three in revenue in Korea.

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AWS Machine Learning Blog

FEBRUARY 19, 2024

Note that you can also use Knowledge Bases for Amazon Bedrock service APIs and the AWS Command Line Interface (AWS CLI) to programmatically create a knowledge base. Create a Lambda function This Lambda function is deployed using an AWS CloudFormation template available in the GitHub repo under the /cfn folder.

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AWS Machine Learning Blog

SEPTEMBER 12, 2024

LangChain is a Python library designed to build applications with LLMs. Prerequisites To implement this solution, you need the following: An AWS account with privileges to create AWS Identity and Access Management (IAM) roles and policies. Basic familiarity with SageMaker and AWS services that support LLMs. Python 3.10

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Flipboard

FEBRUARY 7, 2025

You will execute scripts to create an AWS Identity and Access Management (IAM) role for invoking SageMaker, and a role for your user to create a connector to SageMaker. Python The code has been tested with Python version 3.13. In this walkthrough, you will use a set of scripts to create the preceding architecture and data flow.

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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. Choose Deploy.

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Mlearning.ai

FEBRUARY 22, 2023

We may use AWS SageMaker to preprocess data, train model and make inferences. In this tutorial, I would like to show you a step-by-step method on how to connect AWS SageMaker with the Snowflake environment. But it’s good practice to have a service account that we can store in AWS either in secret key or parameter store.

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AWS Machine Learning Blog

NOVEMBER 26, 2024

We add the following to the end of the prompt: provide the response in json format with the key as “class” and the value as the class of the document We get the following response: { "class": "ID" } You can now read the JSON response using a library of your choice, such as the Python JSON library. The following image is of a gearbox.

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Mlearning.ai

MARCH 15, 2023

Build a Stocks Price Prediction App powered by Snowflake, AWS, Python and Streamlit — Part 2 of 3 A comprehensive guide to develop machine learning applications from start to finish. I have checked the AWS S3 bucket and Snowflake tables for a couple of days and the Data pipeline is working as expected.

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AWS Machine Learning Blog

MAY 22, 2024

Vision-language models Since 2021, there has been a rise in interest in vision-language models (VLMs), which led to the release of solutions such as Contrastive Language-Image Pre-training (CLIP) and Bootstrapping Language-Image Pre-training (BLIP). For details, see Creating an AWS account. medium instance and the Data Science 3.0

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Flipboard

NOVEMBER 24, 2023

This use case highlights how large language models (LLMs) are able to become a translator between human languages (English, Spanish, Arabic, and more) and machine interpretable languages (Python, Java, Scala, SQL, and so on) along with sophisticated internal reasoning.

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AWS Machine Learning Blog

NOVEMBER 15, 2024

For instance, analyzing large tables might require prompting the LLM to generate Python or SQL and running it, rather than passing the tabular data to the LLM. What caused inflation in 2021? We give more details on that aspect later in this post. In practice, the router module can be implemented with an initial LLM call.

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AWS Machine Learning Blog

SEPTEMBER 23, 2024

Amazon Bedrock Knowledge Bases offers a streamlined approach to implement RAG on AWS, providing a fully managed solution for connecting FMs to custom data sources. LangChain is an open source Python library designed to build applications with LLMs. Amazon Bedrock makes this effortless by providing standardized API access to many FMs.

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Towards AI

APRIL 4, 2024

pip install python-dotenv Then, create a file named.env in the root directory of their project. and AWS via Coursera. Yarnit U+007C Generative AI platform for personalized content creation Discover the power of Yarnit.app, the generative AI driven digital content creation platform. To do this, you’ll need to import the libraries.

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AWS Machine Learning Blog

NOVEMBER 14, 2023

The solution also uses Amazon Bedrock , a fully managed service that makes foundation models (FMs) from Amazon and third-party model providers accessible through the AWS Management Console and APIs. Prerequisites For this tutorial, you need a bash terminal with Python 3.9 The source code is available in the GitHub repository.

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Pickl AI

NOVEMBER 27, 2024

Summary : Combining Python and R enriches Data Science workflows by leveraging Python’s Machine Learning and data handling capabilities alongside R’s statistical analysis and visualisation strengths. Python excels in Machine Learning, automation, and data processing, while R shines in statistical analysis and visualisation.

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AWS Machine Learning Blog

NOVEMBER 14, 2023

You can now fine-tune and deploy Mistral text generation models on SageMaker JumpStart using the Amazon SageMaker Studio UI with a few clicks or using the SageMaker Python SDK. You can fine-tune the models using either the SageMaker Studio UI or SageMaker Python SDK. The model is made available under the permissive Apache 2.0

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Mlearning.ai

DECEMBER 22, 2023

Setup Development Environment In this tutorial, we are using a Python notebook outside of Sagemaker studio. You can jump AWS authentication steps if you're already in AWS 's environment. </s> Finally, we can chunk and upload our dataset to S3. cache" }, # set env variable to cache models in /tmp ) Then, the

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AWS Machine Learning Blog

FEBRUARY 25, 2025

In 2021, Applus+ IDIADA , a global partner to the automotive industry with over 30 years of experience supporting customers in product development activities through design, engineering, testing, and homologation services, established the Digital Solutions department. For the classifier, we employ k-NN, using the scikit-learn Python module.

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AWS Machine Learning Blog

MAY 30, 2023

In 2021, we launched AWS Support Proactive Services as part of the AWS Enterprise Support plan. In Part 1 , we showed how to get started using AWS Cost Explorer to identify cost optimization opportunities in SageMaker. In this series of posts, we share lessons learned about optimizing costs in Amazon SageMaker.

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AWS Machine Learning Blog

OCTOBER 30, 2023

You can access the pre-trained models, solution templates, and examples through the SageMaker JumpStart landing page in Amazon SageMaker Studio or use the SageMaker Python SDK. In 2021, he presented a paper on adversarial neural networks at the ICLR conference. He got his master’s degree from Columbia University.

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AWS Machine Learning Blog

JUNE 7, 2023

You can deploy and use the Falcon LLMs with a few clicks in SageMaker Studio or programmatically through the SageMaker Python SDK. For example, GPT-3 (2020) and BLOOM (2022) feature around 175 billion parameters, Gopher (2021) has 230 billion parameters, and MT-NLG (2021) 530 billion parameters. In 2022, Hoffman et al.

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AWS Machine Learning Blog

SEPTEMBER 12, 2023

In 2021, Scalable Capital experienced a tenfold increase of its client base, from tens of thousands to hundreds of thousands. Solution overview Scalable Capital’s ML infrastructure consists of two AWS accounts: one as an environment for the development stage and the other one for the production stage. Use Version 2.x

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AWS Machine Learning Blog

JUNE 7, 2023

billion in Q3 2021 and Q3 2022, and $6 million and $(11.3) billion for the nine months ended September 30, 2021 and 2022. (2) billion as of December 31, 2021 and September 30, 2022, respectively. DataFrame is a popular choice for data manipulation, analysis, and visualization in programming languages such as Python and R.

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Flipboard

FEBRUARY 2, 2023

There are around 3,000 and 4,000 plays from four NFL seasons (2018–2021) for punt and kickoff plays, respectively. GluonTS is a Python package for probabilistic time series modeling, but the SBP distribution is not specific to time series, and we were able to repurpose it for regression.

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AWS Machine Learning Blog

DECEMBER 20, 2023

Because the models are hosted and deployed on AWS, you can rest assured that your data, whether used for evaluating or using the model at scale, is never shared with third parties. AWS does not make any representations, warranties, or guarantees that any information in this guidance will result in a particular outcome or result.

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AWS Machine Learning Blog

FEBRUARY 28, 2023

AWS provides the most complete set of services for the entire end-to-end data journey for all workloads, all types of data, and all desired business outcomes. The high-level steps involved in the solution are as follows: Use AWS Step Functions to orchestrate the health data anonymization pipeline.

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AWS Machine Learning Blog

AUGUST 15, 2023

According to a study, by 2021, videos already make up 81% of all consumer internet traffic. Prerequisites You need an AWS account with an AWS Identity and Access Management (IAM) role with permissions to manage resources created as part of the solution. For details, refer to create an AWS account.

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IBM Journey to AI blog

JANUARY 10, 2023

This data will be analyzed using Netezza SQL and Python code to determine if the flight delays for the first half of 2022 have increased over flight delays compared to earlier periods of time within the current data (January 2019 – December 2021). Any data from June 2003 up until the most recent month of data available can be selected.

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Mlearning.ai

JUNE 14, 2023

Using LLMs Use vs build ($) — Pretrained Vs Train Vs Finetune LLMs Pretraining vs Fine-tuning vs In-context Learning of LLM (GPT-x) EXPLAINED | Ultimate Guide ($) — YouTube Using 3rd party models Proprietary -OpenAI Getting Started with OpenAI API and GPT-3 | Beginner Python Tutorial — YouTube Introduction — OpenAI API Open Source ?

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Hacker News

JUNE 9, 2025

Most modern object-oriented languages, from Objective-C and Go to Java and Python, show the influence of Smalltalk. Conclusion Although Smalltalk wasnt the first object-oriented programming language, Smalltalk introduced the term object-oriented programming and was very influential in later object-oriented programming languages.

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Pickl AI

NOVEMBER 4, 2024

billion in 2021 and is expected to grow at a CAGR of 11.0% from 2021 to 2026. Python Known for its simplicity and versatility, Python is widely used for data manipulation and analysis. It is essential for organisations looking to leverage data from multiple platforms, ensuring consistency and accuracy in reporting.

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Heartbeat

FEBRUARY 27, 2023

Stable Baselines, a top-notch Python implementation of reinforcement learning methods, is another popular framework. AWS, Google Cloud, and Azure are a few well-known cloud service providers that provide pre-built GANs and DRL frameworks for creating and deploying models on their cloud platforms.

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AWS Machine Learning Blog

APRIL 18, 2023

Solution overview In the following sections, we provide a step-by-step demonstration for fine-tuning an LLM for text generation tasks via both the JumpStart Studio UI and Python SDK. We select Amazon’s SEC filing reports for years 2021–2022 as the training data to fine-tune the GPT-J 6B model.

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