Smart Data Collective

MARCH 28, 2022

It can be further classified as statistical and predictive modeling, but the two are closely associated with each other. Prescriptive data analytics: It is used to predict outcomes and necessary subsequent actions by combining the features of big data and AI.

Data Analytics 86

Data Analytics Software Analytics Statistics 86

DataRobot Blog

DECEMBER 1, 2022

Artificial intelligence (AI) can help improve the response rate on your coupon offers by letting you consider the unique characteristics and wide array of data collected online and offline of each customer and presenting them with the most attractive offers. Training and Testing Different AI Models.

Machine Learning 52

Machine Learning Marketing Modeling Statistics 52

IBM Big Data Hub

JULY 5, 2023

It allows the company to run tests and predict performance based on simulations. With a good digital twin, it’s possible to predict how an asset will perform under certain conditions and what it’s projected lifespan will be. A digital twin is a virtual representation of an asset that a company intends to purchase.

Strategy 53

Strategy Management IoT Cost-Benefit 53

Domino Data Lab

OCTOBER 23, 2019

You can add a Makefile command test that will run all of your notebooks by issuing. test: py.test --nbval notebooks/*.ipynb. In addition, having a larger set of data such that the model could be split into test versus training data would ensure better accuracy and reduce the chance of overfitting.

Statistics 59

Statistics Machine Learning Testing Modeling 59

Domino Data Lab

AUGUST 20, 2019

Real-world datasets can be missing values due to the difficulty of collecting complete datasets and because of errors in the data collection process. The problem is that a new unique identifier of a test example won’t be anywhere in the tree. We proceed as usual and see what happens with our training and testing errors.

Testing 68

Testing Modeling Interactive Measurement 68

Domino Data Lab

AUGUST 1, 2021

A comprehensive list of all attributes and symbol codes is given in the document that accompanies the original dataset. We start by loading the data, setting meaningful names for all attributes, and displaying the first 5 entries. After forming the X and y variables, we split the data into training and test sets.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

O'Reilly on Data

MARCH 24, 2020

Beyond the autonomous driving example described, the “garbage in” side of the equation can take many forms—for example, incorrectly entered data, poorly packaged data, and data collected incorrectly, more of which we’ll address below. The model and the data specification become more important than the code.

Machine Learning 352

Machine Learning Statistics Data Quality Modeling 352