The MLOps Blog

JUNE 27, 2023

Alignment to other tools in the organization’s tech stack Consider how well the MLOps tool integrates with your existing tools and workflows, such as data sources, data engineering platforms, code repositories, CI/CD pipelines, monitoring systems, etc. and Pandas or Apache Spark DataFrames.

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AWS Machine Learning Blog

NOVEMBER 16, 2023

Amazon SageMaker provides purpose-built tools for machine learning operations (MLOps) to help automate and standardize processes across the ML lifecycle. In this post, we describe how Philips partnered with AWS to develop AI ToolSuite—a scalable, secure, and compliant ML platform on SageMaker.

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AWS Machine Learning Blog

AUGUST 21, 2023

Amazon SageMaker Data Wrangler reduces the time it takes to collect and prepare data for machine learning (ML) from weeks to minutes. We are happy to announce that SageMaker Data Wrangler now supports using Lake Formation with Amazon EMR to provide this fine-grained data access restriction.

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Alation

SEPTEMBER 23, 2021

The data catalog also stores metadata (data about data, like a conversation), which gives users context on how to use each asset. It offers a broad range of data intelligence solutions, including analytics, data governance, privacy, and cloud transformation. Data Catalog by Type.

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Precisely

SEPTEMBER 26, 2024

Without proper data preparation, you risk issues like bias and hallucination, inaccurate predictions, poor model performance, and more. “If If you do not have AI-ready data, then you’re more than likely to experience some of these challenges,” says Cotroneo. AI systems require high-quality, well-governed data to avoid missteps.

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IBM Journey to AI blog

MARCH 14, 2024

Try Db2 Warehouse SaaS on AWS for free   Netezza SaaS on AWS IBM® Netezza® Performance Server is a cloud-native data warehouse designed to operationalize deep analytics, data mining and BI by unifying, accessing and scaling all types of data across the hybrid cloud. Netezza

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Precisely

JULY 18, 2024

Data management recommendations and data products emerge dynamically from the fabric through automation, activation, and AI/ML analysis of metadata. As data grows exponentially, so do the complexities of managing and leveraging it to fuel AI and analytics.

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Pickl AI

OCTOBER 17, 2024

Tools like Apache NiFi, Talend, and Informatica provide user-friendly interfaces for designing workflows, integrating diverse data sources, and executing ETL processes efficiently. Choosing the right tool based on the organisation’s specific needs, such as data volume and complexity, is vital for optimising ETL efficiency.

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IBM Journey to AI blog

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.

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Heartbeat

MAY 29, 2023

In this article, we will explore the essential steps involved in training LLMs, including data preparation, model selection, hyperparameter tuning, and fine-tuning. We will also discuss best practices for training LLMs, such as using transfer learning, data augmentation, and ensembling methods.

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Pickl AI

DECEMBER 10, 2024

These solutions allow users with minimal technical expertise to automate workflows, integrate disparate datasets, and streamline data preparation. This democratisation of data access empowers cross-functional teams to collaborate effectively on analytics initiatives.

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Pickl AI

OCTOBER 3, 2024

Data Management Tools These platforms often provide robust data management features that assist in data preparation, cleaning, and augmentation, which are crucial for training effective AI models. Organisations must ensure that data is securely stored, transmitted, and processed to prevent potential leaks or misuse12.

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AWS Machine Learning Blog

NOVEMBER 13, 2024

You can now register machine learning (ML) models in Amazon SageMaker Model Registry with Amazon SageMaker Model Cards , making it straightforward to manage governance information for specific model versions directly in SageMaker Model Registry in just a few clicks.

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AWS Machine Learning Blog

MARCH 27, 2025

When implementing machine learning (ML) workflows in Amazon SageMaker Canvas , organizations might need to consider external dependencies required for their specific use cases. Without writing a single line of code, users can explore datasets, transform data, build models, and generate predictions.

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AWS Machine Learning Blog

DECEMBER 18, 2024

With a vision to build a large language model (LLM) trained on Italian data, Fastweb embarked on a journey to make this powerful AI capability available to third parties. She specializes in AI operations, data governance, and cloud architecture on AWS. The team opted for fine-tuning on AWS.

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