AWS Machine Learning Blog

APRIL 18, 2023

One of the major challenges in training and deploying LLMs with billions of parameters is their size, which can make it difficult to fit them into single GPUs, the hardware commonly used for deep learning. Defining hyperparameters involves setting the values for various parameters used during the training process of an ML model.

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AWS Machine Learning Blog

FEBRUARY 10, 2023

Through a collaboration between the Next Gen Stats team and the Amazon ML Solutions Lab , we have developed the machine learning (ML)-powered stat of coverage classification that accurately identifies the defense coverage scheme based on the player tracking data. Journal of machine learning research 9, no.

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AWS Machine Learning Blog

APRIL 18, 2023

One of the major challenges in training and deploying LLMs with billions of parameters is their size, which can make it difficult to fit them into single GPUs, the hardware commonly used for deep learning. Defining hyperparameters involves setting the values for various parameters used during the training process of an ML model.

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Mlearning.ai

MAY 23, 2023

With the advancement of technology, machine learning, and computer vision techniques can be used to develop automated solutions for leaf disease detection. In this article, we will discuss the development of a Leaf Disease Detection Flask App that uses a deep learning model to automatically detect the presence of leaf diseases.

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Mlearning.ai

JUNE 6, 2023

In today’s blog, we will see some very interesting Python Machine Learning projects with source code. This list will consist of Machine learning projects, Deep Learning Projects, Computer Vision Projects , and all other types of interesting projects with source codes also provided. We have the IPL data from 2008 to 2017.

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AWS Machine Learning Blog

APRIL 3, 2023

JumpStart is the machine learning (ML) hub of Amazon SageMaker that offers a one-click access to over 350 built-in algorithms; pre-trained models from TensorFlow, PyTorch, Hugging Face, and MXNet; and pre-built solution templates. This page lists available end-to-end ML solutions, pre-trained models, and example notebooks.

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Mlearning.ai

MAY 21, 2023

With the advancement of technology, machine learning, and computer vision techniques can be used to develop automated solutions for leaf disease detection. In this article, we will discuss the development of a Leaf Disease Detection Flask App that uses a deep learning model to automatically detect the presence of leaf diseases.

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ML Review

MARCH 5, 2019

Journal of machine learning research, 9(Nov), 2579–2605. AI Distillery (Part 2): Distilling by Embedding was originally published in ML Review on Medium, where people are continuing the conversation by highlighting and responding to this story. Information Processing & Management, 24(5), 513–523. Maaten, L. D., & Hinton, G.

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