O'Reilly on Data

APRIL 19, 2021

First, 82% of the respondents are using supervised learning, and 67% are using deep learning. Deep learning is a set of algorithms that are common to almost all AI approaches, so this overlap isn’t surprising. 58% claimed to be using unsupervised learning. form data). Techniques.

Enterprise 356

Enterprise Modeling Risk Manufacturing 356

IBM Big Data Hub

AUGUST 28, 2023

Data extraction Once you’ve assigned numerical values, you will apply one or more text-mining techniques to the structured data to extract insights from social media data. Data analysis and interpretation The next step is to examine the extracted patterns, trends and insights to develop meaningful conclusions.

Data mining 56

Data mining Machine Learning Deep Learning Marketing 56

Ontotext

FEBRUARY 26, 2024

The answers to these foundational questions help you uncover opportunities and detect risks. Further, RED’s underlying model can be visually extended and customized to complex extraction and classification tasks. Why do risk and opportunity events matter? RED answers key questions such as: “What happened?”, “Who was involved?”,

Data-driven 59

Data-driven Risk Modeling Risk Management 59

Domino Data Lab

MARCH 3, 2019

O’Reilly Media had an earlier survey about deep learning tools which showed the top three frameworks to be TensorFlow (61% of all respondents), Keras (25%), and PyTorch (20%)—and note that Keras in this case is likely used as an abstraction layer atop TensorFlow. The data types used in deep learning are interesting.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49