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.

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AWS Machine Learning Blog

MAY 10, 2023

The Jupyter Notebook, first released in 2011, has become a de facto standard tool used by millions of users worldwide across every possible academic, research, and industry sector. Given the importance of Jupyter to data scientists and ML developers, AWS is an active sponsor and contributor to Project Jupyter.

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AWS Machine Learning Blog

JUNE 18, 2024

On December 6 th -8 th 2023, the non-profit organization, Tech to the Rescue , in collaboration with AWS, organized the world’s largest Air Quality Hackathon – aimed at tackling one of the world’s most pressing health and environmental challenges, air pollution. This is done to optimize performance and minimize cost of LLM invocation.

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AWS Machine Learning Blog

DECEMBER 14, 2023

Established in 2011, Talent.com aggregates paid job listings from their clients and public job listings, and has created a unified, easily searchable platform. The system includes feature engineering, deep learning model architecture design, hyperparameter optimization, and model evaluation, where all modules are run using Python.

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AWS Machine Learning Blog

OCTOBER 23, 2023

Founded in 2011, Talent.com is one of the world’s largest sources of employment. The system is developed by a team of dedicated applied machine learning (ML) scientists, ML engineers, and subject matter experts in collaboration between AWS and Talent.com. The recommendation system has driven an 8.6%

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AWS Machine Learning Blog

APRIL 19, 2023

Most publicly available fraud detection datasets don’t provide this information, so we use the Python Faker library to generate a set of transactions covering a 5-month period. Prerequisites We provide an AWS CloudFormation template to create the prerequisite resources for this solution. This dataset contains 5.4

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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. Integration: Strong integration with Python, supporting popular libraries such as NumPy and SciPy. However, for effective use of PyTorch, familiarity with Python and machine learning principles is a must.

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