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How Machine Learning Enhances Momentum of Cryptocurrency Price Movements

Smart Data Collective

A number of new predictive analytics algorithms are making it easier to forecast price movements in the cryptocurrency market. Conversely, if predictive analytics models suggest that the value of a cryptocurrency price is likely to decrease, more investors are likely to sell off their cryptocurrency holdings.

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What is business analytics? Using data to improve business outcomes

CIO Business Intelligence

Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. What are the benefits of business analytics? What is the difference between business analytics and business intelligence? This is the purview of BI.

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Fleet Management and Big Data: Points to Consider

Smart Data Collective

The total amount of new data will increase to 175 zettabytes by 2025 , up from 33 zettabytes in 2018. All in all, the concept of big data is all about predictive analytics. What’s even more important, predictive analytics prevents accidents on the road. So, without further ado, let’s see how it works in detail.

Big Data 143
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18 Examples Of Big Data Analytics In Healthcare That Can Save People

datapine

Now that we live longer, treatment models have changed and many of these changes are namely driven by data. Every patient has his own digital record which includes demographics, medical history, allergies, laboratory test results, etc. and could provide a model for the EU to follow. 8) Predictive Analytics In Healthcare.

Big Data 364
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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

However, businesses today want to go further and predictive analytics is another trend to be closely monitored. Another increasing factor in the future of business intelligence is testing AI in a duel. Industries harness predictive analytics in different ways.

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7 famous analytics and AI disasters

CIO Business Intelligence

MIT Technology Review has chronicled a number of failures, most of which stem from errors in the way the tools were trained or tested. For example, Driggs’ group found that their own model was flawed because it was trained on a data set that included scans of patients that were lying down while scanned and patients that were standing up.

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What is Automated Machine Learning (AutoML)?

Smarten

With the right tools, today’s average business user can become a Citizen Data Scientist , using data integrated from various sources to learn, test theories and make decisions. AutoML comes into play as business users leverage systems and solutions that are designed with Machine Learning capabilities to predict outcomes and analyze data.