DataRobot Blog

JUNE 23, 2022

Your artificial intelligence (AI) system has given you this “predicted feature” in addition to what you already know about the applicant. Business rules set by the credit committee to control business risk and the loan portfolio also constrain accepting this application and advancing the loan. Take Action.

Predictive Modeling 59

Predictive Modeling Modeling Data Science Measurement 59

CIO Business Intelligence

MARCH 5, 2024

CIOs must also partner with CISOs, legal, human resources, and business leaders to build awareness of policies and develop a generative AI risk management strategy. Today, top AI-assistant capabilities delivering results include generating code, test cases, and documentation. So, what delivers on the productivity promise today?

Cost-Benefit 110

Cost-Benefit Advertising Experimentation Software 110

Cloudera

SEPTEMBER 7, 2023

But it’s also fraught with risk. This June, for example, the European Union (EU) passed the world’s first regulatory framework for AI, the AI Act , which categorizes AI applications into “banned practices,” “high-risk systems,” and “other AI systems,” with stringent assessment requirements for “high-risk” AI systems.

Insurance 83

Insurance Risk Data-driven Finance 83

O'Reilly on Data

SEPTEMBER 19, 2023

While data scientists were no longer handling Hadoop-sized workloads, they were trying to build predictive models on a different kind of “large” dataset: so-called “unstructured data.” A single document may represent thousands of features. “Here’s our risk model.

Machine Learning 256

Machine Learning Testing Modeling Cost-Benefit 256

Smart Data Collective

MAY 17, 2021

Legacy solutions might have used paper trails and documents, but that same information is now digital. Predictive models, estimates and identified trends can all be sent to the project management team to speed up their decisions. It can also be used to analyze driver behaviors to optimize fuel stops, personal breaks and more.

Big Data 101

Big Data Cost-Benefit IoT Machine Learning 101

IBM Big Data Hub

DECEMBER 20, 2023

Instead of using explicit instructions for performance optimization, ML models rely on algorithms and statistical models that deploy tasks based on data patterns and inferences. In other words, ML leverages input data to predict outputs, continuously updating outputs as new data becomes available. temperature, salary).

Machine Learning 74

Machine Learning Modeling Deep Learning Predictive Modeling 74

IBM Big Data Hub

JULY 5, 2023

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. Read this blog post to explore how digital twins can help you optimize your asset performance.

Strategy 53

Strategy Management IoT Cost-Benefit 53

Alation

APRIL 14, 2022

They strove to ramp up skills in all manner of predictive modeling, machine learning, AI, or even deep learning. These factors risk data originating in far-flung environments, where the data structures and semantics are not well understood or documented. Problems arise when data sources are semantically incompatible.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

DataRobot Blog

JANUARY 10, 2023

Clinics and hospitals like Phoenix Children’s use AI to predict which patients are at risk of contracting an illness so that they can then prescribe medication and treatment accordingly. Create DataRobot Notebooks in a Centralized Notebook Management Space. These DataRobot features are huge time savers.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

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

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. It provides the occasion for deeper exploration of which inputs that can be influenced and which risks can be proactively managed. Our team does a lot of forecasting.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

Domino Data Lab

JULY 9, 2019

Diving into examples of building and deploying ML models at The New York Times including the descriptive topic modeling-oriented Readerscope (audience insights engine), a prediction model regarding who was likely to subscribe/cancel their subscription, as well as prescriptive example via recommendations of highly curated editorial content.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

O'Reilly on Data

SEPTEMBER 11, 2019

So, we used a form of the Term Frequency-Inverse Document Frequency (TF/IDF) technique to identify and rank the top terms in this year’s Strata NY proposal topics—as well as those for 2018, 2017, and 2016. But the database—or, more precisely, the data model —is no longer the sole or, arguably, the primary focus of data engineering.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

Domino Data Lab

AUGUST 1, 2021

This dataset classifies customers based on a set of attributes into two credit risk groups – good or bad. A comprehensive list of all attributes and symbol codes is given in the document that accompanies the original dataset. PDPs for the bicycle count prediction model (Molnar, 2009). A14 : no checking account.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

datapine

NOVEMBER 27, 2019

This is one of the major trends chosen by Gartner in their 2020 Strategic Technology Trends report , combining AI with autonomous things and hyperautomation, and concentrating on the level of security in which AI risks of developing vulnerable points of attacks. Industries harness predictive analytics in different ways.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Jet Global

SEPTEMBER 1, 2023

But we’re also seeing its use expand in other industries, like Financial Services applications for credit risk assessment or Human Resources applications to identify employee trends. Using the information from predictive analytics can help companies—and business applications—suggest actions that can affect positive operational changes.

Predictive Analytics 52

Predictive Analytics Risk Analytics Software 52

Jet Global

MAY 1, 2023

CEO Priorities Grow revenue and “hit the number” Manage costs and meet profitability goals Attract and retain talent Innovate and out-perform the competition Manage risk Connect the Dots Present embedded analytics as a way to differentiate from the competition and increase revenue. Present your business case.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52