AWS Machine Learning Blog

JUNE 15, 2023

Dive into Deep Learning ( D2L.ai ) is an open-source textbook that makes deep learning accessible to everyone. It features interactive Jupyter notebooks with self-contained code in PyTorch, JAX, TensorFlow, and MXNet, as well as real-world examples, exposition figures, and math.

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AWS Machine Learning Blog

NOVEMBER 15, 2024

Prerequisites To try out this solution using SageMaker JumpStart, you 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. of persons present’ for the sustainability committee meeting held on 5th April, 2012?

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

Examples of other PBAs now available include AWS Inferentia and AWS Trainium , Google TPU, and Graphcore IPU. in 2012 is now widely referred to as ML’s “Cambrian Explosion.” Together, these elements lead to the start of a period of dramatic progress in ML, with NN being redubbed deep learning. Work by Hinton et al.

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Flipboard

AUGUST 17, 2023

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and ML to deliver the best price-performance at any scale. Prerequisites To continue with the examples in this post, you need to create the required AWS resources.

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Mlearning.ai

JUNE 14, 2023

Learning LLMs (Foundational Models) Base Knowledge / Concepts: What is AI, ML and NLP Introduction to ML and AI — MFML Part 1 — YouTube What is NLP (Natural Language Processing)? — YouTube YouTube Introduction to Natural Language Processing (NLP) NLP 2012 Dan Jurafsky and Chris Manning (1.1)

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ODSC - Open Data Science

MAY 1, 2023

.` Hagay Lupesko VP Engineering, MosaicML | Expert in Generative AI Training and Inference, Former Leader at Meta AI and AWS In his role as VP of Engineering, Hagay Lupesko focuses on making generative AI training and inference efficient, fast, and accessible.

Data Science 52

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Mlearning.ai

JUNE 18, 2023

This puts paupers, misers and cheapskates who do not have access to a dedicated deep learning rig or a paid cloud service such as AWS at a disadvantage. In this article we show how to use Google Colab perform transfer learning on YOLO , a well known deep learning computer vision model written in C and CUDA.

Deep Learning 52

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The MLOps Blog

NOVEMBER 30, 2022

These days enterprises are sitting on a pool of data and increasingly employing machine learning and deep learning algorithms to forecast sales, predict customer churn and fraud detection, etc., Most of its products use machine learning or deep learning models for some or all of their features.

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DrivenData Labs

MAY 1, 2025

changes between 2003 and 2012). His contributions include developing and refining machine learning and deep learning models using these datasets and optimizing state-of-the-art large language models. Feature Engineering: We engineered features to capture socio-demographic, temporal, and group-level effects (e.g.,

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AWS Machine Learning Blog

APRIL 15, 2025

Amazon Web Services (AWS) provides highly optimized and cost-effective solutions for deploying AI models, like the Mixtral 8x7B language model, for inference at scale. This post demonstrates how to deploy and serve the Mixtral 8x7B language model on AWS Inferentia2 instances for cost-effective, high-performance inference.

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AWS Machine Learning Blog

OCTOBER 24, 2024

Large language models (LLMs) are very large deep-learning models that are pre-trained on vast amounts of data. In this post, we will explore building a reusable RAG data pipeline on LangChain —an open source framework for building applications based on LLMs—and integrating it with AWS Glue and Amazon OpenSearch Serverless.

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AWS Machine Learning Blog

OCTOBER 11, 2024

You can set up the notebook in any AWS Region where Amazon Bedrock Knowledge Bases is available. You also need an AWS Identity and Access Management (IAM) role assigned to the SageMaker Studio domain. Configure Amazon SageMaker Studio The first step is to set up an Amazon SageMaker Studio notebook to run the code for this post.

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