O'Reilly on Data

JUNE 18, 2019

There has been a significant increase in our ability to build complex AI models for predictions, classifications, and various analytics tasks, and there’s an abundance of (fairly easy-to-use) tools that allow data scientists and analysts to provision complex models within days. Data integration and cleaning.

Machine Learning 259

Machine Learning Data Quality Statistics Modeling 259

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. Computer Science Skills.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

bridgei2i

DECEMBER 15, 2021

With significant adoption among industries as well as personal lives, AI is impacting enterprise transformation at scale, whilst changing the way humans interact with machines. Naturally, the change in consumer behavior prompted media companies to change their business models. Anticipating Demand through Predictive Modelling on OTT.

Recreation/Entertainment 52

Recreation/Entertainment Metadata Advertising Predictive Modeling 52

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. offers many statistics and machine learning abilities.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

DMBS2

DECEMBER 12, 2017

Machine learning and AI have little relevance to most traditional transactional apps. Predictive modeling is a huge deal in customer-relationship apps. The most advanced organizations developing and using those rely on machine learning. Voice interaction is already revolutionary in certain niches (e.g.

Machine Learning 50

Machine Learning Predictive Modeling Deep Learning Modeling 50

Domino Data Lab

OCTOBER 7, 2020

Statistics developed in the last century are based on probability models (distributions). This model for data analytics has proven highly successful in basic biomedical research and clinical trials. The accuracy of any predictive model approaches 100%. Property 4: The accuracy of any predictive model approaches 100%.

Statistics 145

Statistics Testing Predictive Modeling Modeling 145

Domino Data Lab

JULY 9, 2019

Assessing whether a business stakeholder is trying to solve for a problem that is descriptive, predictive, or prescriptive and then re-framing the problem as supervised learning, unsupervised learning, or reinforcement learning, respectively. or a prescriptive model? or a descriptive model?”

Data Science 112

Data Science Machine Learning Advertising Modeling 112

IBM Big Data Hub

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. However, the growing influence of ML isn’t without complications.

Machine Learning 82

Machine Learning Modeling Deep Learning Predictive Modeling 82

Alation

APRIL 14, 2022

And, as organizations progress and grow, “data drift” starts to impact data usage, models, and your business. Supports the ability to interact with the actual data and perform analysis on it. They strove to ramp up skills in all manner of predictive modeling, machine learning, AI, or even deep learning.

Metadata 59

Metadata Data Governance Modeling Data-driven 59