IBM Big Data Hub

JULY 6, 2023

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. appeared first on IBM Blog.

Machine Learning 60

Machine Learning Data Science Statistics Deep Learning 60

datapine

AUGUST 14, 2019

To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations. But being an inquisitive Sherlock Holmes of data is no easy task. In the past, data scientists had to rely on powerful computers to manage large volumes of data.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

IBM Big Data Hub

FEBRUARY 14, 2024

Clean up with predictive maintenance AI can be used for predictive maintenance by analyzing data directly from machinery to identify problems and flag required maintenance. Maintenance schedules can use AI-powered predictive analytics to create greater efficiencies.

Cost-Benefit 88

Cost-Benefit Insurance Unstructured Data Machine Learning 88

IBM Big Data Hub

AUGUST 28, 2023

Text representation In this stage, you’ll assign the data numerical values so it can be processed by machine learning (ML) algorithms, which will create a predictive model from the training inputs. And with advanced software like IBM Watson Assistant , social media data is more powerful than ever.

Data mining 58

Data mining Machine Learning Deep Learning Marketing 58