datapine

AUGUST 14, 2019

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.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

Domino Data Lab

JULY 28, 2021

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. After cleaning, the data is now ready for processing.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

IBM Big Data Hub

JULY 6, 2023

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. An e-commerce conglomeration uses predictive analytics in its recommendation engine. Python is the most common programming language used in machine learning.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

IBM Big Data Hub

MAY 17, 2024

Poorly run implementations of traditional or generative AI technology in commerce—such as deploying deep learning models trained on inadequate or inappropriate data—lead to bad experiences that alienate both consumers and businesses.

B2B 65

B2B Interactive Optimization Forecasting 65

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. See what’s ahead AI can assist with forecasting.

Cost-Benefit 83

Cost-Benefit Insurance Unstructured Data Machine Learning 83

IBM Big Data Hub

DECEMBER 20, 2023

For instance, if data scientists were building a model for tornado forecasting, the input variables might include date, location, temperature, wind flow patterns and more, and the output would be the actual tornado activity recorded for those days. AI studio The post Five machine learning types to know appeared first on IBM Blog.

Machine Learning 74

Machine Learning Modeling Deep Learning Predictive Modeling 74