AWS Machine Learning Blog

APRIL 19, 2024

Solution overview For this demo, we use the SageMaker controller to deploy a copy of the Dolly v2 7B model and a copy of the FLAN-T5 XXL model from the Hugging Face Model Hub on a SageMaker real-time endpoint using the new inference capabilities. Now you also can use them with SageMaker Operators for Kubernetes. or above installed.

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Flipboard

AUGUST 17, 2023

Deploy the CloudFormation template Complete the following steps to deploy the CloudFormation template: Save the CloudFormation template sm-redshift-demo-vpc-cfn-v1.yaml Enter a stack name, such as Demo-Redshift. You should see a new CloudFormation stack with the name Demo-Redshift being created. yaml locally.

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Towards AI

JULY 21, 2023

To further comment on Fury, for those looking to intern in the short term, we have a position available to work in an NLP deep learning project in the healthcare domain. A toolkit that allows the developer to dig deep into language models, in addition to dataset visualization. Broadcaster Stream API Fast.ai What can it do?

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AWS Machine Learning Blog

FEBRUARY 11, 2025

GraphStorm is a low-code enterprise graph machine learning (ML) framework that provides ML practitioners a simple way of building, training, and deploying graph ML solutions on industry-scale graph data. Today, AWS AI released GraphStorm v0.4.

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AWS Machine Learning Blog

OCTOBER 23, 2024

The following demo shows Agent Creator in action. To use Agent Creator effectively, schedule a demo of SnapLogic’s Agent Creator to learn how it can address your specific use cases. He focuses on Deep learning including NLP and Computer Vision domains. He currently is working on Generative AI for data integration.

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AWS Machine Learning Blog

AUGUST 24, 2023

Today, we’re pleased to announce the preview of Amazon SageMaker Profiler , a capability of Amazon SageMaker that provides a detailed view into the AWS compute resources provisioned during training deep learning models on SageMaker. The following table provides the links to the supported AWS Deep Learning Containers for SageMaker.

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AWS Machine Learning Blog

JANUARY 31, 2024

Amazon Titan Text Embeddings is a text embeddings model that converts natural language text—consisting of single words, phrases, or even large documents—into numerical representations that can be used to power use cases such as search, personalization, and clustering based on semantic similarity. Why do we need an embeddings model?

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AWS Machine Learning Blog

NOVEMBER 19, 2024

As attendees circulate through the GAIZ, subject matter experts and Generative AI Innovation Center strategists will be on-hand to share insights, answer questions, present customer stories from an extensive catalog of reference demos, and provide personalized guidance for moving generative AI applications into production.

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AWS Machine Learning Blog

NOVEMBER 1, 2023

The demo implementation code is available in the following GitHub repo. Utilizing the latest Hugging Face LLM modules on Amazon SageMaker, AWS customers can now tap into the power of SageMaker deep learning containers (DLCs). He focuses on developing scalable machine learning algorithms.

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ODSC - Open Data Science

JULY 22, 2023

On both days, we had our AI Expo & Demo Hall where over a dozen of our partners set up to showcase their latest developments, tools, frameworks, and other offerings. Keynotes Our main keynote sessions were held on the virtual side of the conference. You can read the recap here and watch the full keynote here.

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AWS Machine Learning Blog

APRIL 5, 2023

In this phase, you submit a text search query or image search query through the deep learning model (CLIP) to encode as embeddings. For demo purposes, we use approximately 1,600 products. We use the first metadata file in this demo. We use a pretrained ResNet-50 (RN50) model in this demo. bin/bash MODEL_NAME=RN50.pt

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Mlearning.ai

AUGUST 28, 2023

I recently took the Azure Data Scientist Associate certification exam DP-100, thankfully I passed after about 3–4 months for studying the Microsoft Data Science Learning Path and the Coursera Microsoft Azure Data Scientist Associate Specialization. Resources include the: Resource group, Azure ML studio, Azure Compute Cluster.

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DataRobot Blog

JULY 27, 2022

The Demo: Autoscaling with MLOps. In this demo, we are completely unattended. If you want to take this demo and rip out a few parts to incorporate into your production code, you’re free to do so. Admin keys are not required for this demo. There are no web UIs or buttons you need to click.

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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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The MLOps Blog

JUNE 27, 2023

Kubeflow integrates with popular ML frameworks, supports versioning and collaboration, and simplifies the deployment and management of ML pipelines on Kubernetes clusters. Metaflow Metaflow helps data scientists and machine learning engineers build, manage, and deploy data science projects. Check out the Kubeflow documentation.

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phData

JUNE 28, 2023

GPUs (graphics processing units) were initially developed to accelerate digital graphics in gaming and media but later found an important application in machine learning and deep learning. Training a machine learning model on a GPU can be 2-10x faster on a GPU than a traditional CPU and often cheaper.

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AWS Machine Learning Blog

JANUARY 17, 2023

Demo notebook. You can use the demo notebook to send example data to already-deployed model endpoints. The demo notebook quickly allows you to get hands-on experience by querying the example data. After you launch the Churn Prediction with Text solution, open the demo notebook by choosing Use Endpoint in Notebook.

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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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DrivenData Labs

DECEMBER 10, 2023

or GPT-4 arXiv, OpenAlex, CrossRef, NTRS lgarma Topic clustering and visualization, paper recommendation, saved research collections, keyword extraction GPT-3.5 Currently, published research may be spread across a variety of different publishers, including free and open-source ones like those used in many of this challenge's demos (e.g.

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The MLOps Blog

MARCH 28, 2024

TL;DR GPUs can greatly accelerate deep learning model training, as they are specialized for performing the tensor operations at the heart of neural networks. Utilization The GPU utilization metric quantifies how the GPU is engaged during the training of deep-learning models.

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DrivenData Labs

DECEMBER 11, 2024

The startup cost is now lower to deploy everything from a GPU-enabled virtual machine for a one-off experiment to a scalable cluster for real-time model execution. Deep learning - It is hard to overstate how deep learning has transformed data science. Simply being open source does not guarantee this kind of growth.

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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. He focuses on developing scalable machine learning algorithms. Outside of work, he enjoys running and hiking.

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AWS Machine Learning Blog

APRIL 3, 2023

We cover prompts for the following NLP tasks: Text summarization Common sense reasoning Question answering Sentiment classification Translation Pronoun resolution Text generation based on article Imaginary article based on title Code for all the steps in this demo is available in the following notebook.

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ODSC - Open Data Science

APRIL 21, 2023

With its applications in creativity, automation, business, advancements in NLP, and deep learning, the technology isn’t only opening new doors, but igniting the public imagination. Let’s take a look at what’s in store for you at ODSC East this May 9th-11th and what you’ll learn about generative AI when you attend.

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Iguazio

APRIL 24, 2024

Contextual Learning - With their deep learning architecture, LLMs can grasp the nuances of language, including idioms, cultural references and complex syntax. Try out this demo that shows how LLMs and ML models integrate together, with open source MLOps orchestration framework MLRun. Click here.

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AWS Machine Learning Blog

MAY 2, 2023

In this demo, we use a Jumpstart Flan T5 XXL model endpoint. He focuses on developing scalable machine learning algorithms. His research interests are in the area of natural language processing, explainable deep learning on tabular data, and robust analysis of non-parametric space-time clustering.

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AWS Machine Learning Blog

MAY 24, 2023

Completion.execute( sm_endpoint=endpoint_name, prompt="Explain deep learning algorithms to 8th graders", numResults=1, maxTokens=100, temperature=0.01 #subject to reduce “hallucination” by using common words. As an alternative, you can use FAISS , an open-source vector clustering solution for storing vectors.

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The MLOps Blog

JANUARY 30, 2025

See in app Full screen preview Check the documentation Play with an interactive example project Get in touch to go through a custom demo with our engineering team Cyclical cosine schedule Returning to a high learning rate after decaying to a minimum is not a new idea in machine learning.

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DataRobot Blog

DECEMBER 20, 2022

Because our training dataset is multimodal and contains imagery data of residential properties in Madrid, DataRobot used machine learning models that contain deep learning based image featurizers. Watch a demo. See DataRobot in Action.

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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. He focuses on developing scalable machine learning algorithms. Outside of work, he enjoys running and hiking.

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Snorkel AI

FEBRUARY 6, 2023

You could imagine, for deep learning, you need, really, a lot of examples. So, deep learning, similarity search is a very easy, simple, task. But then, well, I’m presenting here, so I probably will have a demo ready, right, to show you. And as you can see, that is a pretty tedious task to do.

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Snorkel AI

FEBRUARY 6, 2023

You could imagine, for deep learning, you need, really, a lot of examples. So, deep learning, similarity search is a very easy, simple, task. But then, well, I’m presenting here, so I probably will have a demo ready, right, to show you. And as you can see, that is a pretty tedious task to do.

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Pickl AI

APRIL 26, 2024

Then, I would use clustering techniques such as k-means or hierarchical clustering to group customers based on similarities in their purchasing behaviour. Are there any areas in data analytics where you want to improve or learn more? Additional Benefits Free demo sessions. Lifetime access to updated learning materials.

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The MLOps Blog

MARCH 21, 2023

An ML platform standardizes the technology stack for your data team around best practices to reduce incidental complexities with machine learning and better enable teams across projects and workflows. We ask this during product demos, user and support calls, and on our MLOps LIVE podcast. Why are you building an ML platform?

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AWS Machine Learning Blog

AUGUST 14, 2023

The code for all the steps in this demo is available in the following notebook. LLMs have demonstrated remarkable capabilities in learning the semantics of natural language and producing human-like responses. He focuses on developing scalable machine learning algorithms. Note that deploying this model requires a p4de.24xlarge

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The MLOps Blog

OCTOBER 3, 2023

What helped me both in the transition to the data scientist role and then also to the MLOps engineer role was doing a combination of boot camps, and when I was going to the MLOps engineer role, I also took this one workshop that’s pretty well-known called Full Stack Deep Learning. I really enjoyed it. How was my code?”

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