IBM Big Data Hub

JULY 6, 2023

Other challenges include communicating results to non-technical stakeholders, ensuring data security, enabling efficient collaboration between data scientists and data engineers, and determining appropriate key performance indicator (KPI) metrics. Healthcare companies are using data science for breast cancer prediction and other uses.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

IBM Big Data Hub

OCTOBER 16, 2023

ML also provides the ability to closely monitor a campaign by checking open and clickthrough rates, among other metrics. Banks and other financial institutions train ML models to recognize suspicious online transactions and other atypical transactions that require further investigation. Many stock market transactions use ML.

Machine Learning 49

Machine Learning Marketing Forecasting Modeling 49

O'Reilly on Data

JANUARY 17, 2023

Building Models. A common task for a data scientist is to build a predictive model. You’ll try this with a few other algorithms, and their respective tuning parameters–maybe even break out TensorFlow to build a custom neural net along the way–and the winning model will be the one that heads to production.

Machine Learning 321

Machine Learning Predictive Modeling Software Modeling 321

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. CIOs and IT leaders are at the center and must decide what copilots to test, who should receive access, and whether experiments are delivering business value.

Cost-Benefit 124

Cost-Benefit Advertising Experimentation Software 124

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 67

Risk ROI Modeling Metrics 67

CIO Business Intelligence

AUGUST 15, 2023

In partnership with OpenAI and Microsoft, CarMax worked to develop, test, and iterate GPT-3 natural language models aimed at achieving those results. The CarMax team also gathered, scrubbed and formatted data from thousands of vehicles to feed into the models, fine-tuning them as the project advanced.

IT 98

IT Manufacturing IoT Cost-Benefit 98

Occam's Razor

NOVEMBER 17, 2008

There is a tendency to think experimentation and testing is optional. Just don't fall for their bashing of all other vendors or their silly claims, false, of "superiority" in terms of running 19 billion combinations of tests or the bonus feature of helping you into your underwear each morning. 4 Big Bets, Low Risks, Happy Customers.

Testing 112

Testing Experimentation Risk Optimization 112

Domino Data Lab

APRIL 21, 2021

Rules-based fraud detection (top) vs. classification decision tree-based detection (bottom): The risk scoring in the former model is calculated using policy-based, manually crafted rules and their corresponding weights. from sklearn import metrics. This is to prevent any information leakage into our test set.

Statistics 69

Statistics Machine Learning Modeling Metrics 69

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 53

Strategy Management IoT Cost-Benefit 53

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

Done right, strategic forecasts can provide insights to decision makers on trends, incorporate forward-looking knowledge of product plans and technology roadmaps when relevant, expose the risks and biases of relying on any one forecasting methodology, and invite input from stakeholders on the uncertainty ranges.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

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. 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.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

Sisense

SEPTEMBER 25, 2020

Linear regression is a form of supervised learning (or predictive modeling). In supervised learning, the dependent variable is predicted from the combination of independent variables. When a single independent variable is used to predict the value of a dependent variable, it’s called simple linear regression.

Statistics 98

Statistics Predictive Modeling Modeling Machine Learning 98

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.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

DataRobot Blog

JUNE 24, 2022

Thanks to the increasingly rapid evolution of AI and advances in machine learning, the real estate industry has a more vivid picture of future risk and opportunities across all different market segments: offices, residential, retail, logistics, hotels, OPRE and data centers.

Forecasting 52

Forecasting Machine Learning Marketing Data-driven 52

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

MAY 1, 2023

As a result, end users can better view shared metrics (backed by accurate data), which ultimately drives performance. CFO Priorities Manage expenses and cash flow Enable profitable growth Contain risk Plan for the future Connect the Dots Do the math. Present your business case. These might be the user stories you construct.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52