DrivenData Labs

MAY 12, 2025

Following the competition, DrivenData worked with the winner and partners at the Max Planck Institute for Evolutionary Anthropology, the Wild Chimpanzee Foundation, and WILDLABS to simplify and adapt the top model in an open source Python package and no-code web application for monitoring wildlife. The full video can be viewed on the website.

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AWS Machine Learning Blog

FEBRUARY 19, 2024

Note that you can also use Knowledge Bases for Amazon Bedrock service APIs and the AWS Command Line Interface (AWS CLI) to programmatically create a knowledge base. Create a Lambda function This Lambda function is deployed using an AWS CloudFormation template available in the GitHub repo under the /cfn folder.

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AWS Machine Learning Blog

MARCH 29, 2023

In this post, we discuss how the IEO developed UNDP’s artificial intelligence and machine learning (ML) platform—named Artificial Intelligence for Development Analytics (AIDA)— in collaboration with AWS, UNDP’s Information and Technology Management Team (UNDP ITM), and the United Nations International Computing Centre (UNICC).

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Flipboard

NOVEMBER 24, 2023

This use case highlights how large language models (LLMs) are able to become a translator between human languages (English, Spanish, Arabic, and more) and machine interpretable languages (Python, Java, Scala, SQL, and so on) along with sophisticated internal reasoning.

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AWS Machine Learning Blog

APRIL 5, 2024

A grid system is established with a 48-meter grid size using Mapbox’s Supermercado Python library at zoom level 19, enabling precise spatial analysis. Among these models, the spatial fixed effect model yielded the highest mean R-squared value, particularly for the timeframe spanning 2014 to 2020.

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AWS Machine Learning Blog

MARCH 23, 2023

This is joint post co-written by Leidos and AWS. Leidos has partnered with AWS to develop an approach to privacy-preserving, confidential machine learning (ML) modeling where you build cloud-enabled, encrypted pipelines. In this session, Feidenbaim describes two prototypes that were built in 2020. resource("s3").Bucket

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ODSC - Open Data Science

AUGUST 4, 2023

Recently, we spoke with Emily Webber, Principal Machine Learning Specialist Solutions Architect at AWS. She’s the author of “Pretrain Vision and Large Language Models in Python: End-to-end techniques for building and deploying foundation models on AWS.” And then I spent many years working with customers.

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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. In 2018, other forms of PBAs became available, and by 2020, PBAs were being widely used for parallel problems, such as training of NN.

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AWS Machine Learning Blog

MAY 25, 2023

in 2020 as a model where parametric memory is a pre-trained seq2seq model and the non-parametric memory is a dense vector index of Wikipedia, accessed with a pre-trained neural retriever. We provide an AWS Cloud Formation template to stand up all the resources required for building this solution.

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AWS Machine Learning Blog

OCTOBER 24, 2023

We discuss IDP in detail in our series Intelligent document processing with AWS AI services ( Part 1 and Part 2 ). Refer to our GitHub repository for detailed Python notebooks and a step-by-step walkthrough. For a step-by-step code walkthrough of Q&A with RAG, refer to the Python notebook on GitHub.

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Towards AI

APRIL 4, 2024

With the release of GPT-3 in May of 2020 and the subsequent improvements in the following months, a whole new set of applications came to the forefront. pip install python-dotenv Then, create a file named.env in the root directory of their project. and AWS via Coursera. To do this, you’ll need to import the libraries.

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AWS Machine Learning Blog

SEPTEMBER 23, 2024

Amazon Bedrock Knowledge Bases offers a streamlined approach to implement RAG on AWS, providing a fully managed solution for connecting FMs to custom data sources. LangChain is an open source Python library designed to build applications with LLMs. nConversely, our Consumer revenue grew dramatically in 2020. No extra characters.

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AWS Machine Learning Blog

JUNE 7, 2023

You can deploy and use the Falcon LLMs with a few clicks in SageMaker Studio or programmatically through the SageMaker Python SDK. In early 2020, research organizations across the world set the emphasis on model size, observing that accuracy correlated with number of parameters.

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AWS Machine Learning Blog

DECEMBER 6, 2023

Second, the ability of these models to generate SQL queries from natural language has been proven for years, as seen in the 2020 release of Amazon QuickSight Q. Deploy the solution To install this solution in your AWS account, complete the following steps: Clone the repository on GitHub. Run npm install to install the dependencies.

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Flipboard

FEBRUARY 2, 2023

GluonTS is a Python package for probabilistic time series modeling, but the SBP distribution is not specific to time series, and we were able to repurpose it for regression. Models were trained and cross-validated on the 2018, 2019, and 2020 seasons and tested on the 2021 season. We used the SBP distribution provided by GluonTS.

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AWS Machine Learning Blog

JULY 31, 2023

IAM policies – Your user should have the AWS Identity and Access Management (IAM) AmazonSageMakerFullAccess policy attached, the ability to build Docker container images to Amazon Elastic Container Registry (Amazon ECR), and FSx for Lustre file systems created. aws s3 cp {estimator_openfold.model_data} openfold_output/model.tar.gz !tar

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Women in Big Data

MAY 21, 2024

Launched in 2015 and becoming a nonprofit organization in 2020, WiBD is a grassroots initiative dedicated to inspiring, connecting, and advancing women in data fields. Preparation: Completed the Data Engineer in Python track, dedicating at least one hour a day to study and take notes. She joined us to share her experience.

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Heartbeat

FEBRUARY 27, 2023

Generative Adversarial Networks, on the other hand, have also been applied to a variety of problems in the healthcare, finance, and entertainment industries, including game design, drug research, and portfolio management (Manaswi, 2020). Types of GANs GANs come in a variety of forms, each having special qualities and applications. Mirza, M.,

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IBM Journey to AI blog

JANUARY 10, 2023

This data will be analyzed using Netezza SQL and Python code to determine if the flight delays for the first half of 2022 have increased over flight delays compared to earlier periods of time within the current data (January 2019 – December 2021). Any data from June 2003 up until the most recent month of data available can be selected.

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AWS Machine Learning Blog

APRIL 3, 2023

A myriad of instruction tuning research has been performed since 2020, producing a collection of various tasks, templates, and methods. SageMaker Python SDK Finally, you can programmatically deploy an endpoint through the SageMaker SDK. He works with Machine Learning Startups to build and deploy AI/ML applications on AWS.

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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. We serve developers and enterprises of all sizes through AWS, which offers a broad set of global compute, storage, database, and other service offerings.

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Snorkel AI

MAY 25, 2023

Next, OpenAI released GPT-3 in June of 2020. LLaMA wasn’t a direct duplication of GPT-3 (Meta AI had introduced their direct GPT-3 clone, OPT-175B , in May of 2020). The plot was boring and the acting was awful: Negative This movie was okay. At 175 billion parameters, GPT-3 set the new size standard for large language models.

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Snorkel AI

MAY 25, 2023

Next, OpenAI released GPT-3 in June of 2020. LLaMA wasn’t a direct duplication of GPT-3 (Meta AI had introduced their direct GPT-3 clone, OPT-175B , in May of 2020). The plot was boring and the acting was awful: Negative This movie was okay. At 175 billion parameters, GPT-3 set the new size standard for large language models.

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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. We serve developers and enterprises of all sizes through AWS, which offers a broad set of global compute, storage, database, and other service offerings.

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AWS Machine Learning Blog

SEPTEMBER 30, 2024

In this blog post, we will show you how to leverage AI21 Labs’ Task-Specific Models (TSMs) on AWS to enhance your business operations. You will learn the steps to subscribe to AI21 Labs in the AWS Marketplace, set up a domain in Amazon SageMaker, and utilize AI21 TSMs via SageMaker JumpStart. Limits are account and resource specific.

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AWS Machine Learning Blog

SEPTEMBER 18, 2023

This post shows how Arup partnered with AWS to perform earth observation analysis with Amazon SageMaker geospatial capabilities to unlock UHI insights from satellite imagery. Arup addressed this challenge by partnering with AWS and using SageMaker geospatial capabilities to enable analysis at a city scale and beyond.

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AWS Machine Learning Blog

AUGUST 14, 2023

In this post and accompanying notebook, we demonstrate how to deploy the BloomZ 176B foundation model using the SageMaker Python simplified SDK in Amazon SageMaker JumpStart as an endpoint and use it for various natural language processing (NLP) tasks. You can also access the foundation models thru Amazon SageMaker Studio.

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AWS Machine Learning Blog

FEBRUARY 5, 2024

This notebook enables direct visualization and processing of geospatial data within a Python notebook environment. With the GPU-powered interactive visualizer and Python notebooks, it’s possible to explore millions of data points in one view, facilitating the collaborative exploration of insights and results.

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Flipboard

JANUARY 15, 2025

The AWS global backbone network is the critical foundation enabling reliable and secure service delivery across AWS Regions. Specifically, we need to predict how changes to one part of the AWS global backbone network might affect traffic patterns and performance across the entire system.

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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. data # Assing local directory path to a python variable local_data_path = "./data/" On the Domains page, open your domain.

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O'Reilly Media

NOVEMBER 26, 2024

In 2020, the World Economic Forum estimated that automation will displace 85 million jobs by 2025 but will also create 97 million new jobs. Examples of these skills are artificial intelligence (prompt engineering, GPT, and PyTorch), cloud (Amazon EC2, AWS Lambda, and Microsoft’s Azure AZ-900 certification), Rust, and MLOps.

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AWS Machine Learning Blog

NOVEMBER 26, 2024

We add the following to the end of the prompt: provide the response in json format with the key as “class” and the value as the class of the document We get the following response: { "class": "ID" } You can now read the JSON response using a library of your choice, such as the Python JSON library. The following image is of a gearbox.

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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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