Jet Global

JULY 25, 2025

Predictive analytics models are created to evaluate past data, uncover patterns, analyze trends, and leverage that insight for forecasting future trends. Predictive analytics tools are powered by several different models and algorithms that can be applied to a wide range of use cases.

Predictive Analytics

datapine

NOVEMBER 27, 2019

The rise of self-service analytics democratized the data product chain. 2019 was a particularly major year for the business intelligence industry. According to Gartner, poor data quality is estimated to cost organizations an average of $15 million per year in losses. Industries harness predictive analytics in different ways.

Business Intelligence

Cloudera

FEBRUARY 16, 2022

Before we can understand how model lineage is managed and subsequently audited, we first need to understand some high-level constructs within CML. The highest level construct in CML is a workspace. Each project consists of a declarative series of steps or operations that define the data science workflow.

Machine Learning

Domino Data Lab

AUGUST 22, 2019

While the field of computational linguistics, or Natural Language Processing (NLP), has been around for decades, the increased interest in and use of deep learning models has also propelled applications of NLP forward within industry. Utilizing NLP helps researchers and data scientists complete core tasks faster. and 11.7).].

Deep Learning

CIO Business Intelligence

AUGUST 15, 2023

From healthcare to manufacturing, this year’s award winners span a wide range of industries, proving once again the impact information technology has in reshaping business and society at large. In partnership with OpenAI and Microsoft, CarMax worked to develop, test, and iterate GPT-3 natural language models aimed at achieving those results.

IT

Insight

FEBRUARY 19, 2020

Using variability in machine learning predictions as a proxy for risk can help studio executives and producers decide whether or not to green light a film project Photo by Kyle Smith on Unsplash Originally posted on Toward Data Science. I held out 20% of this as a test set and used the remainder for training and validation.

Risk