A fintech startup was struggling to continue operating due to 20% of its transactions being fraudulent. Find out how this organization used the Darwin platform to build a machine learning model to detect fraud without any data science expertise.
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"The time reduction in the modeling testing is the most valuable thing at the moment. The time that Darwin saves for us to be constantly testing the model has been a game changer for us."
The use of machine learning in data-driven organizations has always been about acting upon knowledge to create a competitive advantage, not the science itself. In this webinar discover how automated
Darwin automates time-consuming tasks ranging from model creation and optimization to model deployment and continuous maintenance.
Machine learning methods are highly dependent on the quality of the data they receive as input, but data preparation and cleaning can be an unwieldy task, taking up 60% of data scientists' time.
Most autoML solutions in the market focus on searching for the best algorithm to fit a given data set. However, these methods lack the ability to produce novel, elegant model architectures.
Automated machine learning has the potential to reduce the burden on overwhelmed teams by automating the bottlenecks in the data science process. But just having an algorithm isn't enough.
Learn how machine learning systems can help lenders identify and track more variables to build a more accurate picture of a customer's financial state. The video goes through practical examples of how
We hope your fantasy league's first week was spectacular. If not, don’t lose hope; even the 2010 Seattle Seahawks made the playoffs with a losing record. Even better, you have Darwin on your team!
Football season couldn’t come fast enough, and now you can’t wait to pummel your office buddies with a stacked roster under your mildly inappropriate team name. However, the competition is fierce...
Darwin™️ is an automated model building product that allows you to go from data to model in less time than traditional methods, enabling the rapid prototyping of scenarios and extraction of insights.
Watch this on-demand webinar to learn how to harness the power of machine learning so you can move from data to results at a staggering speed. During this quick 30 minutes the SparkCognition team d
Common neural network architectures may work well for known, established data problems; however, they can fall short when modern machine learning applications demand more performance and higher levels
With AMB, lenders can expect an increase in loans offered, with optimized interest pricing and lower defaults, and a forecasted 20% ROI.
With the power of NLP and auto ML a major telecom provider expects to reduce complaint call volume by 33%, all while increasing brand loyalty.
This video shows how Darwin, an automated model building tool, empowers data scientists by using historical data sets to build a model that detects fraudulent transactions.
This video shows how Darwin, an automated model building tool, empowers data scientists by using historical data sets to build a model that predicts insurance pricing.