DataRobot Blog

DECEMBER 15, 2022

While AI-powered forecasting can help retailers implement sales and demand forecasting—this process is very complex, and even highly data-driven companies face key challenges: Scale: Thousands of item combinations make it difficult to manually build predictive models. The Leaderboard of trained models—ordered based on your metric.

Forecasting 81

Forecasting Modeling ROI Machine Learning 81

DataRobot Blog

DECEMBER 1, 2022

As you upload your data, DataRobot will do some initial exploratory data analysis to get a deeper understanding of the dataset prior to model training. Next, choose your target variable—in this instance it is automatically detected as a classification problem and an optimization metric is recommended. Automate Feature Engineering.

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 55

Strategy Management IoT Cost-Benefit 55

DataRobot Blog

JANUARY 10, 2023

Most, if not all, machine learning (ML) models in production today were born in notebooks before they were put into production. In addition, code intelligence capabilities, including autocomplete and inline documentation for each function, are accessible via simple keyboard shortcuts.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

A single model may also not shed light on the uncertainty range we actually face. For example, we may prefer one model to generate a range, but use a second scenario-based model to “stress test” the range. Over the life of the forecast, the data scientist will publish historical accuracy metrics.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

Domino Data Lab

AUGUST 22, 2019

There are steps you can take to preprocess natural language data such that the modeling you carry out downstream may be more accurate. Common natural language preprocessing options include: Tokenization: This is the splitting of a document (e.g., Execute gutenberg.fileids() to print the names of all 18 documents.)

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

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. One of the things this data set doesn’t have, however, is a single metric to rank both offensive and defensive performance in a single statistic. In Figure 6.8, Collecting Wikipedia Pageviews for Athletes.

Statistics 59

Statistics Machine Learning Testing Modeling 59

Rocket-Powered Data Science

SEPTEMBER 20, 2021

We would be able to go far beyond searching for correctly spelled column headings in databases or specific keywords in data documentation, to find the data we needed (assuming we even knew the correct labels, metatags, and keywords used by the dataset creators). That’s data democratization. That’s insights democratization.

Data Science 285

Data Science Forecasting Business Intelligence Sales 285

Occam's Razor

NOVEMBER 18, 2014

Short story #2: Predictive Modeling, Quantifying Cost of Inaction. You can hover over each box to get a sense of the key metrics. Short story #2: Predictive Modeling, Quantifying Cost of Inaction. Thank goodness for predictive models. Short story #1: Treemaps, Sunbursts, Packed Trees, Oh My!

Visualization 143

Visualization Slice and Dice Predictive Modeling Metrics 143

Domino Data Lab

AUGUST 1, 2021

Intrinsic methods – this technique is based on ANNs that have been designed to output an explanation alongside the standard prediction. Because of its architecture, intrinsically explainable ANNs can be optimised not just on its prediction performance, but also on its explainability metric. A14 : no checking account.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

datapine

NOVEMBER 27, 2019

However, businesses today want to go further and predictive analytics is another trend to be closely monitored. Another increasing factor in the future of business intelligence is testing AI in a duel. The predictive models, in practice, use mathematical models to predict future happenings, in other words, forecast engines.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Jet Global

MAY 1, 2023

As a result, end users can better view shared metrics (backed by accurate data), which ultimately drives performance. When treating a patient, a doctor may wish to study the patient’s vital metrics in comparison to those of their peer group. They can also create custom calculations and metrics, and build new data visualizations.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52