Remove Deep Learning Remove Forecasting Remove Predictive Analytics Remove Unstructured Data
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Top Data Science Tools That Will Empower Your Data Exploration Processes

datapine

Data science tools are used for drilling down into complex data by extracting, processing, and analyzing structured or unstructured data to effectively generate useful information while combining computer science, statistics, predictive analytics, and deep learning. Source: mathworks.com.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

One ride-hailing transportation company uses big data analytics to predict supply and demand, so they can have drivers at the most popular locations in real time. The company also uses data science in forecasting, global intelligence, mapping, pricing and other business decisions.

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The most valuable AI use cases for business

IBM Big Data Hub

Maintenance schedules can use AI-powered predictive analytics to create greater efficiencies. See what’s ahead AI can assist with forecasting. For example, a supply-chain function can use algorithms to predict future needs and the time products need to be shipped for timely arrival.

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Top 10 IT & Technology Buzzwords You Won’t Be Able To Avoid In 2020

datapine

An important part of artificial intelligence comprises machine learning, and more specifically deep learning – that trend promises more powerful and fast machine learning. An exemplary application of this trend would be Artificial Neural Networks (ANN) – the predictive analytics method of analyzing data.

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Biggest Trends in Data Visualization Taking Shape in 2022

Smart Data Collective

There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. This is something that you can learn more about in just about any technology blog. We would like to talk about data visualization and its role in the big data movement.