Domino Data Lab

OCTOBER 7, 2020

In this blog we show what the changes in behavior of data are in high dimensions. In our next blog we discuss how we try to avoid these problems in applied data analysis of high dimensional data. Statistics developed in the last century are based on probability models (distributions). Data Has Properties. data = simData.y)

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Statistics Testing Predictive Modeling Modeling 145

IBM Big Data Hub

OCTOBER 16, 2023

Machine learning in financial transactions ML and deep learning are widely used in banking, for example, in fraud detection. Banks and other financial institutions train ML models to recognize suspicious online transactions and other atypical transactions that require further investigation.

Machine Learning 52

Machine Learning Marketing Forecasting Modeling 52

Cloudera

FEBRUARY 16, 2022

The greater our understanding of how a model works, the better we are able to predict what the output will be for a range of inputs or changes to the model’s parameters. Given the complexity of some ML models, especially those based on Deep Learning (DL) Convolutional Neural Networks (CNNs), there are limits to interpretability.

Machine Learning 81

Machine Learning Modeling Metadata Recreation/Entertainment 81

IBM Big Data Hub

FEBRUARY 14, 2024

AI platforms can use machine learning and deep learning to spot suspicious or anomalous transactions. Banks and other lenders can use ML classification algorithms and predictive models to suggest loan decisions.

Cost-Benefit 88

Cost-Benefit Insurance Unstructured Data Machine Learning 88

Smarten

APRIL 19, 2024

Assisted Predictive Modeling and Auto Insights to create predictive models using self-guiding UI wizard and auto-recommendations The Future of AI in Analytics The C=suite executive survey revealed that 93% felt that data strategy is critical to getting value from generative AI, but a full 57% had made no changes to their data.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

O'Reilly on Data

MARCH 20, 2019

The objective here is to brainstorm on potential security vulnerabilities and defenses in the context of popular, traditional predictive modeling systems, such as linear and tree-based models trained on static data sets. If an attacker can receive many predictions from your model API or other endpoint (website, app, etc.),

Modeling 222

Modeling Machine Learning Predictive Modeling Consulting 222

IBM Big Data Hub

DECEMBER 20, 2023

Unsupervised machine learning Unsupervised learning algorithms—like Apriori, Gaussian Mixture Models (GMMs) and principal component analysis (PCA)—draw inferences from unlabeled datasets, facilitating exploratory data analysis and enabling pattern recognition and predictive modeling.

Machine Learning 82

Machine Learning Modeling Deep Learning Predictive Modeling 82

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.

Forecasting 81

Forecasting Modeling ROI Machine Learning 81

Domino Data Lab

APRIL 21, 2021

deep learning) there is no guaranteed explainability. In this blog post we will show an implementation of an ML-based anomaly detection based on XGBoost. We will go through a typical ML pipeline, where we do data ingestion, exploratory data analysis, feature engineering, model training and evaluation. doi: 10.1109/TKDE.2008.239.

Statistics 69

Statistics Machine Learning Modeling Metrics 69

Alation

APRIL 14, 2022

They strove to ramp up skills in all manner of predictive modeling, machine learning, AI, or even deep learning. Subscribe to Alation's Blog. Organizations launched initiatives to be “ data-driven ” (though we at Hired Brains Research prefer the term “data-aware”).

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Domino Data Lab

AUGUST 1, 2021

The interest in interpretation of machine learning has been rapidly accelerating in the last decade. This can be attributed to the popularity that machine learning algorithms, and more specifically deep learning, has been gaining in various domains. Methods for explaining Deep Learning.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

O'Reilly on Data

MARCH 24, 2020

By Wansink’s own admission in the blog post, that’s not what happened in his lab.” A bright future would see data preparation and data quality as first-class citizens in the data workflow, alongside machine learning, deep learning, and AI.

Machine Learning 346

Machine Learning Statistics Data Quality Modeling 346