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3 Things Citizen Data Scientists Need in Predictive Analytics!

Smarten

When combined with Citizen Data Scientist initiatives, the adoption and use of predictive modeling and forecasting techniques can be a boon to any enterprise. Team members who have access to augmented analytics and assisted predictive modeling can plan better, predict more accurately and dependably meet goals and objectives.

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Seven Steps to Success for Predictive Analytics in Financial Services

Birst BI

A personal crystal ball that predicts your days ahead is what financial services firms everywhere want. Every day, these companies pose questions such as: Will this new client provide a good return on investment, relative to the potential risk? Is this existing client a termination risk? Will this next trade return a profit?

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Plug n’ Play Predictive Analytics for Your Business

Smarten

How Can Assistive Predictive Modeling Help My Business Users? If you are wondering how and why predictive analytics software has expanded into the self-serve business user market, the reason is simple. Predictive Analytics Software should be easy to implement, easy to personalize and easy to use.

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How to Leverage Machine Learning for AML Compliance

BizAcuity

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. In fact, online casinos as an industry carries the biggest risk of money laundering. There are primarily two underlying techniques that can be leveraged for AML initiatives- Exploratory Data Analysis and Predictive analytics.

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How to Leverage Machine Learning for AML Compliance

BizAcuity

Anti-Money Laundering (AML) is increasingly becoming a crucial branch of risk management and fraud prevention. In fact, online casinos as an industry carries the biggest risk of money laundering. There are primarily two underlying techniques that can be leveraged for AML initiatives- Exploratory Data Analysis and Predictive analytics.

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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

Diagnostic analytics uses data (often generated via descriptive analytics) to discover the factors or reasons for past performance. Predictive analytics applies techniques such as statistical modeling, forecasting, and machine learning to the output of descriptive and diagnostic analytics to make predictions about future outcomes.

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3 Key Components of the Interdisciplinary Field of Data Science

Domino Data Lab

There are many software packages that allow anyone to build a predictive model, but without expertise in math and statistics, a practitioner runs the risk of creating a faulty, unethical, and even possibly illegal data science application. All models are not made equal.