Model 
CIO
APRIL 26, 2024
Once completed within two years, the platform, OneTru, will give TransUnion and its customers access to TransUnion’s behemoth trove of consumer data to fuel next-generation analytical services, machine learning models and generative AI applications, says Achanta, who is driving the effort, and held similar posts at Neustar and Walmart.
Xebia
APRIL 2, 2024
After months of crunching data, plotting distributions, and testing out various machine learning algorithms you have finally proven to your stakeholders that your model can deliver business value. Your model has to leave the comforts of your development environment and is ready to move to production to be consumed by the end user.
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CIO
NOVEMBER 16, 2023
A large language model (LLM) is a type of gen AI that focuses on text and code instead of images or audio, although some have begun to integrate different modalities. But there’s a problem with it — you can never be sure if the information you upload won’t be used to train the next generation of the model. It’s not trivial,” she says.
TechCrunch
DECEMBER 7, 2023
It appears that the allure of complex pricing models and business strategies often proves too tempting to resist. © 2023 TechCrunch. All rights reserved. For personal use only.
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Discover a streamlined methodical approach to Apache Cassandra® data modeling. Are you a developer, database architect, or database administrator that's new to Cassandra, but been tasked with developing a plan for implementing the technology anyway? Worry no more.
TechCrunch
SEPTEMBER 4, 2023
Large language models (LLMs) like OpenAI’s ChatGPT all suffer from the same problem: they make stuff up. The mistakes range from strange and innocuous — like claiming that the Golden Gate Bridge was transported across Egypt in 2016 — to highly problematic, even dangerous.
CIO
MARCH 6, 2024
What has IT’s role been in the transformation to a SaaS model? We built that end-to-end data model and process from scratch while we ran the old business. We knew we had a unique opportunity to build a new end-to-end architecture with a common AI-powered data model. Today, we’re a $1.6 Today, we’re a $1.6
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Apache Kafka is a powerful piece of software that can solve a lot of problems. Like most libraries and frameworks, you get out of it what you put into it. Learn 10 rules that will help you perfect your Kafka system to get ahead.
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Choosing software to bake into your architecture is a long-term decision and it is important to understand all the implications of your choice. Learn three key areas that should be considered when evaluating a particular open source project.
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As machine learning models are put into production and used to make critical business decisions, the primary challenge becomes operation and management of multiple models.
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The guide includes a checklist, an assessment, industry-specific use cases, and a data & analytics maturity model and roadmap. Download this guide for practical advice on using a semantic layer to improve data literacy and scale self-service analytics.
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How to choose the appropriate fairness and bias metrics to prioritize for your machine learning models. How to successfully navigate the bias versus accuracy trade-off for final model selection and much more. Download this guide to find out: How to build an end-to-end process of identifying, investigating, and mitigating bias in AI.
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Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.
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How to improve model accuracy with training data. Get the information you need to ensure your evaluation experience is efficient and yields the data you need to make your purchasing decision. In this solution brief, you will learn: The differences between 1st generation, 2nd generation, and modern-day ASR solutions.
Advertiser: Data Robot
Ultimately, the market will demand an extensive ecosystem, and tools will need to streamline data and model utilization and management across multiple environments. Enterprise interest in the technology is high, and the market is expected to gain momentum as organizations move from prototypes to actual project deployments.
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