AWS Machine Learning Blog

OCTOBER 23, 2024

Agent Creator is a versatile extension to the SnapLogic platform that is compatible with modern databases, APIs, and even legacy mainframe systems, fostering seamless integration across various data environments. The following demo shows Agent Creator in action. Chunker Snap – Segments large texts into manageable pieces.

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Flipboard

DECEMBER 11, 2024

Second, because data, code, and other development artifacts like machine learning (ML) models are stored within different services, it can be cumbersome for users to understand how they interact with each other and make changes. With the SQL editor, you can query data lakes, databases, data warehouses, and federated data sources.

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IBM Journey to AI blog

MARCH 14, 2024

Also, traditional database management tasks, including backups, upgrades and routine maintenance drain valuable time and resources, hindering innovation. By using fit-for-purpose databases, customers can efficiently run workloads, using the appropriate engine at the optimal cost to optimize analytics for the best price-performance.

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Iguazio

APRIL 28, 2025

You can hear more details in the webinar this article is based on, straight from Kaegan Casey, AI/ML Solutions Architect at Seagate. Iguazio allows sharing projects between diverse teams, provides detailed logging of parameters, metrics, and ML artifacts and allows for artifact versioning including labels, tags, associated data etc.

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AWS Machine Learning Blog

DECEMBER 15, 2023

We are excited to announce the launch of Amazon DocumentDB (with MongoDB compatibility) integration with Amazon SageMaker Canvas , allowing Amazon DocumentDB customers to build and use generative AI and machine learning (ML) solutions without writing code. Enter a connection name such as demo and choose your desired Amazon DocumentDB cluster.

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Flipboard

NOVEMBER 24, 2023

The SnapLogic Intelligent Integration Platform (IIP) enables organizations to realize enterprise-wide automation by connecting their entire ecosystem of applications, databases, big data, machines and devices, APIs, and more with pre-built, intelligent connectors called Snaps.

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The MLOps Blog

JULY 4, 2024

TL;DR Vector databases play a key role in Retrieval-Augmented Generation (RAG) systems. Further, talking to data scientists and ML engineers, I noticed quite a bit of confusion around RAG systems and terminology. Vector Database: A database purpose-built for handling storage and retrieval of vectors.

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AWS Machine Learning Blog

NOVEMBER 7, 2023

Instead of relying solely on their pre-trained knowledge, RAG allows models to pull data from documents, databases, and more. This means that as new data becomes available, it can be added to the retrieval database without needing to retrain the entire model. Memory efficiency – LLMs require significant memory to store parameters.

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The MLOps Blog

MAY 10, 2023

When working on real-world machine learning (ML) use cases, finding the best algorithm/model is not the end of your responsibilities. Reusability & reproducibility: Building ML models is time-consuming by nature. Save vs package vs store ML models Although all these terms look similar, they are not the same.

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phData

MAY 17, 2024

The brand-new Forecasting tool created on Snowflake Data Cloud Cortex ML allows you to do just that. What is Cortex ML, and Why Does it Matter? Cortex ML is Snowflake’s newest feature, added to enhance the ease of use and low-code functionality of your business’s machine learning needs.

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The MLOps Blog

JUNE 27, 2023

Knowledge and skills in the organization Evaluate the level of expertise and experience of your ML team and choose a tool that matches their skill set and learning curve. Model monitoring and performance tracking : Platforms should include capabilities to monitor and track the performance of deployed ML models in real-time.

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Tableau

DECEMBER 1, 2021

Chris had earned an undergraduate computer science degree from Simon Fraser University and had worked as a database-oriented software engineer. In 2004, Tableau got both an initial series A of venture funding and Tableau’s first EOM contract with the database company Hyperion—that’s when I was hired. Release v1.0

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AWS Machine Learning Blog

JANUARY 31, 2024

Embeddings play a key role in natural language processing (NLP) and machine learning (ML). This technique is achieved through the use of ML algorithms that enable the understanding of the meaning and context of data (semantic relationships) and the learning of complex relationships and patterns within the data (syntactic relationships).

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Iguazio

APRIL 24, 2024

Generative AI is by no means a replacement for the previous wave of AI/ML (now sometimes referred to as ‘traditional AI/ML’), which continues to deliver significant value, and represents a distinct approach with its own advantages. In the end, we explain how MLOps can help accelerate the process and bring these models to production.

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ODSC - Open Data Science

OCTOBER 19, 2023

Grab one for access to Keynote Talks, Demo Talks, the AI Expo and Demo Hall, and Extra Events. Find Your AI Solutions at the ODSC West AI Expo Learn about the best AI solutions for your organization at the ODSC West AI Expo & Demo Hall during these Demo Theater sessions! Attend in-person or virtually!

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Mlearning.ai

JUNE 26, 2023

Introduction Deepchecks is a groundbreaking open-source Python package that aims to simplify and enhance the process of implementing automated testing for machine learning (ML) models. In this article, we will explore the various aspects of Deepchecks and how it can revolutionize the way we validate and maintain ML models.

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ODSC - Open Data Science

APRIL 28, 2025

As AI systems grow more complex, combining ML models, LLMs, and open-source tools into Composite AI, ensuring reliability is mission-critical. Perfect for ML/AI engineers aiming to build robust, production-grade LLM systems across chatbots, RAG, and enterprise apps.

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Flipboard

JULY 24, 2023

It is also called the second brain as it can store data that is not arranged according to a present data model or schema and, therefore, cannot be stored in a traditional relational database or RDBMS. It has an official website from which you can access the premium version of Quivr by clicking on the button ‘Try demo.’

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AWS Machine Learning Blog

FEBRUARY 29, 2024

Amazon SageMaker Studio offers a comprehensive set of capabilities for machine learning (ML) practitioners and data scientists. These include a fully managed AI development environment with an integrated development environment (IDE), simplifying the end-to-end ML workflow.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

This solution employs machine learning (ML) for anomaly detection, and doesn’t require users to have prior AI expertise. The application, once deployed, constructs an ML model using the Random Cut Forest (RCF) algorithm. He is dedicated to making ML and generative AI more accessible and applying them to solve challenging problems.

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Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody. Everybody can train a model.

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Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody. Everybody can train a model.

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Iguazio

JULY 22, 2024

MongoDB for end-to-end AI data management MongoDB Atlas , an integrated suite of data services centered around a multi-cloud NoSQL database, enables developers to unify operational, analytical, and AI data services to streamline building AI-enriched applications. Additionally, compliance requirements and evolving regulations (e.g.

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AWS Machine Learning Blog

DECEMBER 14, 2023

In November 2022, we announced that AWS customers can generate images from text with Stable Diffusion models in Amazon SageMaker JumpStart , a machine learning (ML) hub offering models, algorithms, and solutions. When it comes to building the essential vector database, AWS provides a multitude of options through their native services.

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Flipboard

FEBRUARY 7, 2023

Amazon SageMaker Studio Lab provides no-cost access to a machine learning (ML) development environment to everyone with an email address. Therefore, you can scale your ML experiments beyond the free compute limitations of Studio Lab and use more powerful compute instances with much bigger datasets on your AWS accounts.

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IBM Journey to AI blog

APRIL 8, 2024

The new Amazon Relational Database Service (Amazon RDS) for Db2 offering allows customers to migrate their existing, self-managed Db2 databases to the cloud and accelerate strategic modernization initiatives. AWS ran a live demo to show how to get started in just a few clicks. Where can I provide feedback?   4. . Amazon RDS

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AWS Machine Learning Blog

JUNE 29, 2023

Some of these solutions use common machine learning (ML) models built on historical interaction patterns, user demographic attributes, product similarities, and group behavior. Amazon Personalize enables developers to build applications powered by the same type of ML technology used by Amazon.com for real-time personalized recommendations.

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The MLOps Blog

JUNE 4, 2024

TL;DR Using CI/CD workflows to run ML experiments ensures their reproducibility, as all the required information has to be contained under version control. The compute resources offered by GitHub Actions directly are not suitable for larger-scale ML workloads. ML experiments are, by nature, full of uncertainty and surprises.

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AWS Machine Learning Blog

APRIL 19, 2024

These controllers allow Kubernetes users to provision AWS resources like buckets, databases, or message queues simply by using the Kubernetes API. About the Authors Rajesh Ramchander is a Principal ML Engineer in Professional Services at AWS. Release v1.2.9 They are also supported by AWS CloudFormation.

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AWS Machine Learning Blog

MAY 13, 2024

Evaluating LLMs is an undervalued part of the machine learning (ML) pipeline. Dataset The MIMIC Chest X-ray (MIMIC-CXR) Database v2.0.0 Context is providing relevant background to ensure the model understands the task or query, such as the schema of a database in the example of natural language querying.

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AWS Machine Learning Blog

AUGUST 8, 2024

Create two users in your Box account For this example, you need two demo users in your Box account in addition to the admin user. Complete the following steps to create these two demo users, using the same email addresses you used when setting up these users in IAM Identity Center: Log in to your Box Enterprise Admin Console as an admin user.

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ODSC - Open Data Science

OCTOBER 24, 2024

The Essential Tools for ML Evaluation and Responsible AI There are lots of checkmarks to hit when developing responsible AI, but thankfully, there are many tools for ML evaluation and frameworks designed to support responsible AI development and evaluation.

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Iguazio

MAY 29, 2024

In the application pipeline, teams can swap: Logging inputs + responses to various data sources (database, stream, file, etc.) Classical ML models and LLMs If using QLORA to fine-tune, teams can swap out domain specific fine tuned adapters while using the same base model (e.g. Additional data sources (RAG, web search, etc.)

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phData

NOVEMBER 28, 2024

“ Vector Databases are completely different from your cloud data warehouse.” – You might have heard that statement if you are involved in creating vector embeddings for your RAG-based Gen AI applications. Enhanced Search and Retrieval Augmented Generation: Vector search systems work by matching queries with embeddings in a database.

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AWS Machine Learning Blog

FEBRUARY 29, 2024

Knowledge Bases is completely serverless, so you don’t need to manage any infrastructure, and when using Knowledge Bases, you’re only charged for the models, vector databases and storage you use. Build a knowledge base for Amazon Bedrock In this section, we demo the process of creating a knowledge base for Amazon Bedrock via the console.

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ODSC - Open Data Science

APRIL 6, 2023

It’s a foundational skill for working with relational databases Just about every data scientist or analyst will have to work with relational databases in their careers. Another boon for efficient work that SQL provides is its simple and consistent syntax that allows for collaboration across multiple databases.

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phData

DECEMBER 16, 2024

This international gathering of practitioners brought together an impressive array of minds striving to advance the science of deploying Machine Learning (ML) and AI models into production. The session included a demo on running a vLLM server for your own large language model (LLM) inference service using Modal.

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