AWS Machine Learning Blog

NOVEMBER 22, 2023

The task involved writing Python code to read data, transform it, and then visualize it in an interesting map. You’ll need access to an AWS account with an access key or AWS Identity and Access Management (IAM) role with permissions to Amazon Bedrock and Amazon Location. The following are a few of the prompts we included.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

In terms of resulting speedups, the approximate order is programming hardware, then programming against PBA APIs, then programming in an unmanaged language such as C++, then a managed language such as Python. Examples of other PBAs now available include AWS Inferentia and AWS Trainium , Google TPU, and Graphcore IPU.

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Towards AI

AUGUST 8, 2024

It can also be used in a variety of languages, such as Python, C++, JavaScript, and Java. Other Cloud Providers: TensorFlow works well with other cloud platforms such as AWS and Azure, supporting scalable deployment and training in cloud environments. The basic data structure for TensorFlow are tensors.

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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. She is focused on building machine learning–based services for AWS customers.

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DagsHub

JULY 25, 2024

A good understanding of Python and machine learning concepts is recommended to fully leverage TensorFlow's capabilities. Further Reading TensorFlow Documentation TensorFlow Tutorials PyTorch PyTorch, developed by Facebook's AI Research Lab (FAIR) , was released in 2016. It is well-suited for both research and production environments.

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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. The Companys net income attributable to the Company for the year ended December 31, 2016 was $4,816,000, or $0.28

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Mlearning.ai

JULY 9, 2023

Abstract Polars is a fast-growing open-source data frame library that is rapidly becoming the preferred choice for data scientists and data engineers in Python. It is available in multiple languages: Python, Rust, and NodeJS. If you are looking for a fast and intuitive data frame library for Python, then Polars is a great option.

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DagsHub

APRIL 7, 2024

The project was created in 2014 by Airbnb and has been developed by the Apache Software Foundation since 2016. Thanks to its various operators, it is integrated with Python, Spark, Bash, SQL, and more. Programming language: It offers a simple way to transform Python code into an interactive workflow application.

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Pickl AI

AUGUST 22, 2024

First released in 2016, it quickly gained traction due to its intuitive design and robust capabilities. Discover its dynamic computational graphs, ease of debugging, strong community support, and seamless integration with popular Python libraries for enhanced development.

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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. The Companys net income attributable to the Company for the year ended December 31, 2016 was $4,816,000, or $0.28

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Explosion

AUGUST 1, 2019

Based on the (fairly vague) marketing copy, AWS might be doing something similar in SageMaker. 2019) have shown that a transformer models trained on only 1% of the IMDB sentiment analysis data (just a few dozen examples) can exceed the pre-2016 state-of-the-art. Modern transfer learning techniques are bearing this out.

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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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