AWS Machine Learning Blog

OCTOBER 20, 2023

Meesho was founded in 2015 and today focuses on buyers and sellers across India. We used AWS machine learning (ML) services like Amazon SageMaker to develop a powerful generalized feed ranker (GFR). In the following sections, we discuss each component and the AWS services used in more detail.

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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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Towards AI

APRIL 19, 2024

Amazon (AWS) 👉Industry domain: Online retail and web services provider 👉Location: Over 175 Amazon fulfillment centers globally 👉Year founded: 1994 👉Key Products developed: Amazon Bedrock, Q, Code Whisperer, Sage Maker 👉Benefits: Fully managed generative AI service options, AWS free tier for experimentation 7.

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AWS Machine Learning Blog

OCTOBER 9, 2023

Also, we need to set up the right permissions using AWS Identity and Access Management (IAM) for Amazon Personalize and Amazon SageMaker service roles so that they can access the needed functionalities. For this post, we choose Python (User-Defined Function). We can do this by adding a Custom transform step. DOI= [link]

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AWS Machine Learning Blog

AUGUST 11, 2023

You will learn how to use the SageMaker Jumpstart UI and SageMaker Python SDK to deploy the solution and run inference using the available models. Note that by following the steps in this section, you will deploy infrastructure to your AWS account that may incur costs. Choose Deploy to create a SageMaker endpoint.

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Towards AI

AUGUST 8, 2024

Developed by Google in 2015, TensorFlow boasts extensive capabilities, resulting in the tool being used often for research purposes or companies using it for their programming purposes. It can also be used in a variety of languages, such as Python, C++, JavaScript, and Java.

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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

NOVEMBER 21, 2023

python -m pip install -q amazon-textract-prettyprinter You have the option to format the text in markdown format, exclude text from within figures in the document, and exclude page header, footer, and page number extractions from the linearized output. At this event, SPIE member Light and Light-based Technologies (IYL 2015).

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DagsHub

JULY 25, 2024

TensorFlow The Google Brain team created the open-source deep learning framework TensorFlow, which was made available in 2015. A good understanding of Python and machine learning concepts is recommended to fully leverage TensorFlow's capabilities. Before using Keras, ensure you have a basic understanding of Python and neural networks.

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Women in Big Data

MAY 21, 2024

Launched in 2015 and becoming a nonprofit organization in 2020, WiBD is a grassroots initiative dedicated to inspiring, connecting, and advancing women in data fields. Preparation: Completed the Data Engineer in Python track, dedicating at least one hour a day to study and take notes. She joined us to share her experience.

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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. per diluted share, for the year ended December 31, 2015. per diluted share, for the year ended December 31, 2015.

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Pickl AI

AUGUST 22, 2024

Discover its dynamic computational graphs, ease of debugging, strong community support, and seamless integration with popular Python libraries for enhanced development. Pythonic Nature PyTorch is designed to be intuitive and closely resembles standard Python programming.

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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. per diluted share, for the year ended December 31, 2015. per diluted share, for the year ended December 31, 2015.

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AWS Machine Learning Blog

FEBRUARY 11, 2025

This model was predominantly trained on AWS, and AWS will also be the first cloud provider to make it available to customers. Models hosted on JumpStart can be provisioned on dedicated SageMaker Inference instances, including AWS Trainium and AWS Inferentia based instances, and are isolated within your virtual private cloud (VPC).

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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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AWS Machine Learning Blog

NOVEMBER 11, 2024

Prerequisites To try out this solution using SageMaker JumpStart, you’ll need the following prerequisites: An AWS account that will contain all of your AWS resources. An AWS Identity and Access Management (IAM) role to access SageMaker. We then also cover how to fine-tune the model using SageMaker Python SDK.

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