Explorium Resources
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Read the blogExplorium Announces $31M in Series B Funding to Accelerate Growth
Explorium is changing the way companies find and use data for superior machine learning models and business decisions.
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Where's the Weakest Link? Understanding Risk in Supply Networks
In our interconnected, globalized world, it’s harder and harder to track the weak spots in your supply chain. That’s why we created this handy guide to understanding and mitigating supply chain risk.
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Read the blogTurning Data from a Cost Center into an Asset
Many organizations see data acquisition and management as a business expense. You may hear questions like, what does it cost to collect and capture this data? The post Turning Data from a Cost...
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Start Small and Scale Smart: Do You Need a Data Science Team, Platform, or Service?
There’s no one way to start using data science. This guide walks you through the pros and cons of each approach and discusses how to allocate your budget efficiently.
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Read the blogCould Machine Learning Help Tom Haverford Save Entertainment 720?
Machine learning is a key tool for improving marketing. Let's break down how Tom Haverford from Parks and Recreation could have used it to save e720.
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Read the blogDomain Knowledge in Data Science: Are Your Models Ready for Business?
In this in-depth article, we explain how the right questions will help you get the domain knowledge you need for data science for business.
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Read the blogHow Will Data Privacy Look in The Future?
Data privacy continues to be a major hurdle for risk officers. In this article, we explain how the global increase in data surveillance creates short term opportunities but long term risks.
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Read the blogHow To Communicate Your Marketing Questions for Data Scientists
Marketing data science has the power to transform businesses. However, for success, marketers need to know how to communicate their goals properly.
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How to Deploy and Future-Proof Your Models: From Theory to Production
It’s no secret that while most organizations understand the importance of machine learning, most initiatives never make it off the ground. Follow this guide to guarantee you make it to production.
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Read the blogCould ML-Powered Risk Models Really Spot OZARK’s Schemes?
In some ways, OZARK’s main plot seems too good to be true, and it might actually be. In the real world where ML-powered risk models exist, could Marty Byrde really get away with his schemes?
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Read the blogReframing the Connection Between Data Science and Automation
Automation and data science are a match made in heaven. It's up to data leaders to understand how to introduce it to their teams in the right way.
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Read the blogWhat Happens When The Definition of Risk Changes?
Risk and probability are based on data. You establish the statistical risk of losing an investment based on other investments that didn’t work out. You assess The post What Happens When The...
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Read the blogAsking the Right Questions: How Machine Learning Improves Your Insights
In this article, we explain how the data science revolution is all about asking questions that get precise answers for the future.
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Read the blogHow to Navigate the New Data Science and Machine Learning Landscape
In this article, we explain how to turn the biggest data science challenges of the moment into business opportunities.
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How Can You Enhance Your Risk Models? Finding Better Signals to Feed Them
In this in-depth guide, we reveal the real reasons your machine learning risk models are falling short, what you can do to fix them — and exactly how to tackle the problem.
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Read the blogThe Three Skills You Need to Instill in Your Data Science Team
To succeed in the data science field, you need more than just technical acumen. We reveal the secrets to making your team indispensable.
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6 Steps to Jumpstart Machine Learning Using the Resources You Already Have
ML has gone from buzzword to business necessity, and implementing it is quickly becoming mandatory. Here are 6 easy steps to follow to get going with the resources you have.
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Read the blogHow Dynamic Risk Modeling Gives Your Detection a Boost
Dynamic risk models add a dimension to rules-based risk modeling that makes you more agile to the changing world.
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35:14Watch videoWebinar: Stay Ahead of the Competition with Better Predictive Power
Learn how automated data discovery removes the time and resource constraints in traditional data acquisition and keeps you ahead of the competition with more powerful insights.
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Read the blogWhy You Need Data Catalogs, Not Databases
When it comes to external data for machine learning, data catalogs provide a handful of time-saving benefits over databases. Learn more.
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