Smart Data Collective

MARCH 23, 2022

The automotive market penetration of AI has increased by 100% since 2015. In July of 2015, two hackers managed to remotely take complete control of a Jeep Cherokee while it was driving on the highway. Utilizing advanced heuristics and AI modeling OEMs can simulate a multitude of conditions, fast-tracking these models using automation.

IoT 110

IoT Internet of Things Testing Cost-Benefit 110

CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. Predictive analytics is often considered a type of “advanced analytics,” and frequently depends on machine learning and/or deep learning.

Data Analytics 125

Data Analytics Diagnostic Analytics Management Analytics 125

DMBS2

DECEMBER 12, 2017

Most of my comments about artificial intelligence in December, 2015 still hold true. Predictive modeling is a huge deal in customer-relationship apps. They have access to lots of data for model training. But there are a few points I’d like to add, reiterate or amplify. They have deep pockets.

Machine Learning 50

Machine Learning Predictive Modeling Deep Learning Modeling 50

The Unofficial Google Data Science Blog

MARCH 31, 2016

KUEHNEL, and ALI NASIRI AMINI In this post, we give a brief introduction to random effects models, and discuss some of their uses. Through simulation we illustrate issues with model fitting techniques that depend on matrix factorization. Random effects models are a useful tool for both exploratory analyses and prediction problems.

Modeling 40

Modeling Statistics Advertising Testing 40

Domino Data Lab

AUGUST 1, 2021

In this article we cover explainability for black-box models and show how to use different methods from the Skater framework to provide insights into the inner workings of a simple credit scoring neural network model. The interest in interpretation of machine learning has been rapidly accelerating in the last decade. See Ribeiro et al.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

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. One of the ways I frame that is, “Are you looking to build a predictive model?

Data Science 112

Data Science Machine Learning Advertising Modeling 112

CIO Business Intelligence

JUNE 5, 2024

In 2015, Major League Baseball revolutionized a sport already known for its sophisticated use of data with MLB Statcast, a tracking technology that collects enormous amounts of game data. We were the go-to guys for any ML or predictive modeling at that time, but looking back it was very primitive.”

Optimization 97

Optimization Predictive Modeling Data-driven Modeling 97