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Join DataRobot at Big Data & AI Paris 2022

DataRobot

Leading French organizations are recognizing the power of AI to accelerate the impact of data science. Since 2016, DataRobot has aligned with customers in finance, retail, healthcare, insurance and more industries in France with great success, with the first customers being leaders in the insurance space. . Chief Data Officer, Matmut.

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AI Chihuahua! Part I: Why Machine Learning is Dogged by Failure and Delays

d2iq

Going from a prototype to production is perilous when it comes to machine learning: most initiatives fail , and for the few models that are ever deployed, it takes many months to do so. As little as 5% of the code of production machine learning systems is the model itself. Adapted from Sculley et al.

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DBeaver takes $6M seed investment to build on growing popularity

TechCrunch

CEO Tatiana Krupenya says that it’s an administrative tool that allows anyone to access data from a variety of sources. Krupenya says this capability puts data administration in reach of not just the most technical data engineers, but also people in other lines of business roles, who normally might not have access to tools like this. “So

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Forget the Rules, Listen to the Data

Hu's Place - HitachiVantara

Rule-based fraud detection software is being replaced or augmented by machine-learning algorithms that do a better job of recognizing fraud patterns that can be correlated across several data sources. DataOps is required to engineer and prepare the data so that the machine learning algorithms can be efficient and effective.

Data 90
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Five Trends for 2019

Hu's Place - HitachiVantara

Public cloud, agile methodologies and devops, RESTful APIs, containers, analytics and machine learning are being adopted. ” Deployments of large data hubs have only resulted in more data silos that are not easily understood, related, or shared.

Trends 86
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5 Positions Companies Need To Navigate Digital Transformation

N2Growth Blog

Sundar Pichai, Google CEO, October 2016. Artificial Intelligence (AI) is at a tipping point, leading a watershed shift to digital intelligence by discovering previously unseen patterns, drawing new inferences, and identifying new relationships from vast amounts of data. Systems Engineer. Data Analyst.

Company 86
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DataOps: Adjusting DevOps for Analytics Product Development

Altexsoft

Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. DataOps is a relatively new methodology that knits together data engineering, data analytics, and DevOps to deliver high-quality data products as fast as possible.