Dataversity

SEPTEMBER 24, 2024

Generative AI (GenAI), specifically as it pertains to the public availability of large language models (LLMs), is a relatively new business tool, so it’s understandable that some might be skeptical of a technology that can generate professional documents or organize data instantly across multiple repositories.

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AWS Machine Learning Blog

NOVEMBER 13, 2024

It helps organizations comply with regulations, manage risks, and maintain operational efficiency through robust model lifecycles and data quality management. Prepare the data to build your model training pipeline. It helps with reproducibility and debugging, making it straightforward to understand and address issues.

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ML ML AWS Data Preparation 120

Dataconomy

MAY 15, 2025

Together AI, the leading AI Acceleration Cloud, has acquired Refuel.ai, a specialist in transforming unstructured data into structured datasets for AI applications, to accelerate the development of production-grade AI applications. The acquisition was announced on May 15, 2025, in San Francisco.

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Pickl AI

JULY 24, 2024

Summary: Data quality is a fundamental aspect of Machine Learning. Poor-quality data leads to biased and unreliable models, while high-quality data enables accurate predictions and insights. What is Data Quality in Machine Learning? Bias in data can result in unfair and discriminatory outcomes.

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ODSC - Open Data Science

APRIL 25, 2023

Hands-on Data-Centric AI: Data Preparation Tuning — Why and How? Be sure to check out her talk, “ Hands-on Data-Centric AI: Data preparation tuning — why and how? Nevertheless, we haven’t yet nailed the process of building a successful and business-meaningful AI solution.

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Data Preparation Machine Learning Machine Learning Data Quality 52

Snorkel AI

DECEMBER 2, 2024

The integration between the Snorkel Flow AI data development platform and AWS’s robust AI infrastructure empowers enterprises to streamline LLM evaluation and fine-tuning, transforming raw data into actionable insights and competitive advantages. Here’s what that looks like in practice.

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Dataconomy

APRIL 29, 2025

Transfer learning applications Utilizing transfer learning allows developers to leverage pre-existing models, improving performance in new contexts while minimizing the need for large amounts of data. Skew transformation Data preparation techniques play a vital role in addressing training-serving skew effectively.

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Dataconomy

MARCH 20, 2025

These platforms provide developers with powerful tools to harness the capabilities of LLMs, improving interaction quality and overall user experience. As AI technologies continue to evolve, understanding the functionalities and development stages of LLM applications is essential for both new and seasoned developers.

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Flipboard

APRIL 30, 2025

million in seed funding to transform how businesses prepare data for AI, promising to save data scientists from the task that consumes 80% of their time. Brooklyn-based Structify emerges from stealth with $4.1 Read More

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IBM Journey to AI blog

JULY 30, 2024

Generative artificial intelligence (gen AI) is transforming the business world by creating new opportunities for innovation, productivity and efficiency. This guide offers a clear roadmap for businesses to begin their gen AI journey. Most teams should include at least four types of team members.

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DagsHub

FEBRUARY 29, 2024

Data, is therefore, essential to the quality and performance of machine learning models. This makes data preparation for machine learning all the more critical, so that the models generate reliable and accurate predictions and drive business value for the organization. million per year.

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AWS Machine Learning Blog

NOVEMBER 1, 2024

Fine-tuning is a powerful approach in natural language processing (NLP) and generative AI , allowing businesses to tailor pre-trained large language models (LLMs) for specific tasks. By fine-tuning, the LLM can adapt its knowledge base to specific data and tasks, resulting in enhanced task-specific capabilities.

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IBM Data Science in Practice

NOVEMBER 28, 2022

Ensuring high-quality data A crucial aspect of downstream consumption is data quality. Studies have shown that 80% of time is spent on data preparation and cleansing, leaving only 20% of time for data analytics. This leaves more time for data analysis.

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AWS Machine Learning Blog

DECEMBER 1, 2023

Additionally, these tools provide a comprehensive solution for faster workflows, enabling the following: Faster data preparation – SageMaker Canvas has over 300 built-in transformations and the ability to use natural language that can accelerate data preparation and making data ready for model building.

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Machine Learning Machine Learning Data Preparation ML 125

Pickl AI

DECEMBER 3, 2024

Summary: Generative AI is transforming Data Analytics by automating repetitive tasks, enhancing predictive modelling, and generating synthetic data. By leveraging GenAI, businesses can personalize customer experiences and improve data quality while maintaining privacy and compliance. What is Generative AI?

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AWS Machine Learning Blog

JUNE 3, 2024

In a single visual interface, you can complete each step of a data preparation workflow: data selection, cleansing, exploration, visualization, and processing. Custom Spark commands can also expand the over 300 built-in data transformations. We start from creating a data flow. SageMaker Data Wrangler will open.

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AWS Machine Learning Blog

NOVEMBER 14, 2024

Use case governance is essential to help ensure that AI systems are developed and used in ways that respect values, rights, and regulations. According to the EU AI Act, use case governance refers to the process of overseeing and managing the development, deployment, and use of AI systems in specific contexts or applications.

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AWS Machine Learning Blog

SEPTEMBER 9, 2024

Generative artificial intelligence (AI) has revolutionized this by allowing users to interact with data through natural language queries, providing instant insights and visualizations without needing technical expertise. This can democratize data access and speed up analysis. powered by Amazon Bedrock Domo.AI experience.

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AWS Machine Learning Blog

MAY 1, 2025

Best practices for data preparation The quality and structure of your training data fundamentally determine the success of fine-tuning. Our experiments revealed several critical insights for preparing effective multimodal datasets: Data structure You should use a single image per example rather than multiple images.

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Dataconomy

MARCH 26, 2025

Fine-tuning plays a crucial role in enhancing the utility of pretrained models in machine learning and AI. This process not only accelerates development but also democratizes access to advanced AI capabilities. What is fine-tuning in machine learning and AI?

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Towards AI

AUGUST 16, 2023

Last Updated on August 17, 2023 by Editorial Team Author(s): Jeff Holmes MS MSCS Originally published on Towards AI. This article is intended as an outline of the key differences rather than a comprehensive discussion on the topic of the AI software process. MLOps is the intersection of Machine Learning, DevOps, and Data Engineering.

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AWS Machine Learning Blog

AUGUST 21, 2024

Choose Data Wrangler in the navigation pane. On the Import and prepare dropdown menu, choose Tabular. A new data flow is created on the Data Wrangler console. Choose Get data insights to identify potential data quality issues and get recommendations. For Analysis name , enter a name.

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Machine Learning Machine Learning Data Governance ML 128

Dataconomy

MARCH 27, 2023

RPA is often considered a form of artificial intelligence, but it is not a complete AI solution. AI, on the other hand, can learn from data and adapt to new situations without human intervention. On the other hand, ML requires a significant amount of data preparation and model training before it can be deployed.

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ML ML Machine Learning Machine Learning 133

Dataconomy

APRIL 14, 2025

As organizations continue to pursue advanced analytics and AI-driven solutions, the demand for effective orchestration becomes increasingly evident. ML orchestration refers to the coordinated management of tasks within the machine learning lifecycle, encompassing processes such as data preparation, model training, validation, and deployment.

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ML ML Machine Learning Machine Learning 91

AWS Machine Learning Blog

FEBRUARY 18, 2025

Recognizing this challenge as an opportunity for innovation, F1 partnered with Amazon Web Services (AWS) to develop an AI-driven solution using Amazon Bedrock to streamline issue resolution. Creating ETL pipelines to transform log data Preparing your data to provide quality results is the first step in an AI project.

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IBM Journey to AI blog

DECEMBER 7, 2023

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. As AI techniques continue to evolve, innovative applications in the OLAP domain are anticipated.

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Flipboard

MARCH 22, 2023

Snowflake is an AWS Partner with multiple AWS accreditations, including AWS competencies in machine learning (ML), retail, and data and analytics. You can import data from multiple data sources, such as Amazon Simple Storage Service (Amazon S3), Amazon Athena , Amazon Redshift , Amazon EMR , and Snowflake.

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Towards AI

FEBRUARY 17, 2025

Originally published on Towards AI. RAFT vs Fine-Tuning Image created by author As the use of large language models (LLMs) grows within businesses, to automate tasks, analyse data, and engage with customers; adapting these models to specific needs (e.g., Data Quality Problem: Biased or outdated training data affects the output.

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Database Data Pipeline Data Preparation Data Quality 89

Towards AI

DECEMBER 19, 2024

Last Updated on December 20, 2024 by Editorial Team Author(s): Towards AI Editorial Team Originally published on Towards AI. You might also enjoy the practical tutorials on building an AI research agent using Pydantic AI and the step-by-step guide on fine-tuning the PaliGemma2 model for object detection. Enjoy the read!

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Database AI AI Data Preparation 104

The MLOps Blog

JUNE 27, 2023

See also Thoughtworks’s guide to Evaluating MLOps Platforms End-to-end MLOps platforms End-to-end MLOps platforms provide a unified ecosystem that streamlines the entire ML workflow, from data preparation and model development to deployment and monitoring. Might be useful Unlike manual, homegrown, or open-source solutions, neptune.ai

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Machine Learning Machine Learning ML ML 134

IBM Journey to AI blog

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

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Tableau

APRIL 18, 2022

We’ve infused our values into our platform, which supports data fabric designs with a data management layer right inside our platform, helping you break down silos and streamline support for the entire data and analytics life cycle. . Analytics data catalog. Data quality and lineage. Data modeling.

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Tableau

APRIL 18, 2022

We’ve infused our values into our platform, which supports data fabric designs with a data management layer right inside our platform, helping you break down silos and streamline support for the entire data and analytics life cycle. . Analytics data catalog. Data quality and lineage. Data modeling.

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Tableau Data Quality Analytics Analytics 98

AWS Machine Learning Blog

NOVEMBER 16, 2023

One of the key drivers of Philips’ innovation strategy is artificial intelligence (AI), which enables the creation of smart and personalized products and services that can improve health outcomes, enhance customer experience, and optimize operational efficiency.

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AWS Machine Learning Blog

JUNE 23, 2023

Amazon SageMaker Data Wrangler is a single visual interface that reduces the time required to prepare data and perform feature engineering from weeks to minutes with the ability to select and clean data, create features, and automate data preparation in machine learning (ML) workflows without writing any code.

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Pickl AI

JUNE 23, 2023

In the world of artificial intelligence (AI), data plays a crucial role. It is the lifeblood that fuels AI algorithms and enables machines to learn and make intelligent decisions. And to effectively harness the power of data, organizations are adopting data-centric architectures in AI. text, images, videos).

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AI AI Data Governance Data Quality 52

ODSC - Open Data Science

MARCH 13, 2023

Machine learning practitioners are often working with data at the beginning and during the full stack of things, so they see a lot of workflow/pipeline development, data wrangling, and data preparation. You can also get data science training on-demand wherever you are with our Ai+ Training platform.

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