Smarten

MAY 29, 2023

World-renowned technology analysis firm Gartner defines the role this way, ‘A citizen data scientist is a person who creates or generates models that leverage predictive or prescriptive analytics, but whose primary job function is outside of the field of statistics and analytics. ‘If Automatic generation of models.

Prescriptive Analytics 52

Prescriptive Analytics Predictive Modeling Digital Transformation Business Objectives 52

O'Reilly on Data

MAY 18, 2020

This article answers these questions, based on our combined experience as both a lawyer and a data scientist responding to cybersecurity incidents, crafting legal frameworks to manage the risks of AI, and building sophisticated interpretable models to mitigate risk. All predictive models are wrong at times?—just

Risk 359

Risk Modeling Data Processing Software 359

Smarten

APRIL 12, 2023

About Smarten The Smarten approach to business intelligence and business analytics focuses on the business user and provides Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.

Snapshot 52

Snapshot Key Performance Indicator KPI Business Intelligence 52

Smarten

JUNE 29, 2018

This article discusses the Paired Sample T Test method of hypothesis testing and analysis. What is the Paired Sample T Test? The Paired Sample T Test is used to determine whether the mean of a dependent variable e.g., weight, anxiety level, salary, reaction time, etc., is the same in two related groups.

Business Analysis 40

Business Analysis Testing Statistics Advertising 40

Smarten

JUNE 17, 2022

After completion of the testing procedure, the certificate is provided to show that all requirements were met. As a certified CERT-IN service and product provider, Smarten adds additional security assurances to its already rich foundation of security measures and methodologies to support clients, partners and stakeholders.

Analytics 67

Analytics IT Business Intelligence Predictive Modeling 67

CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. Predictive analytics is often considered a type of “advanced analytics,” and frequently depends on machine learning and/or deep learning.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

BizAcuity

APRIL 1, 2023

Predictive modeling for flagging suspicious activity Predictive analytics can be used to analyze past customer behavior and transactions to identify patterns that may indicate potential money laundering activity. Building a predictive model is a continuous process and commitment. This is not the final step.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

Domino Data Lab

OCTOBER 7, 2020

The Curse of Dimensionality , or Large P, Small N, ((P >> N)) , problem applies to the latter case of lots of variables measured on a relatively few number of samples. MANOVA, for example, can test if the heights and weights in boys and girls is different. The accuracy of any predictive model approaches 100%.

Statistics 145

Statistics Testing Predictive Modeling Modeling 145

BizAcuity

JANUARY 18, 2023

Predictive modeling for flagging suspicious activity. Predictive analytics can be used to analyze past customer behavior and transactions to identify patterns that may indicate potential money laundering activity. Steps to building a highly accurate predictive model for AML. These include-.

Machine Learning 52

Machine Learning Predictive Analytics Predictive Modeling Risk 52

Smarten

JUNE 29, 2018

This article focuses on the Independent Samples T Test technique of Hypothesis testing. What is the Independent Samples T Test Method of Hypothesis Testing? Let’s look at a sample of the Independent t-test on two variables. One is a dimension containing two values and the other is a measure. About Smarten.

Testing 40

Testing Statistics IT Business Intelligence 40

DataRobot

MAY 25, 2021

DataRobot is excited to be awarded the 2021 ACT-IAC Innovation Award for ContagionNET, our pioneering rapid antigen test for COVID-19 that is at the forefront of pandemic preparedness and response. As part of these efforts, we built accurate predictive models to determine the spread of the disease weeks and months in advance of a surge.

Testing 52

Testing Predictive Modeling Data-driven Reporting 52

Paul Blogs on BI

MARCH 25, 2020

This first metric requires people to be tested and, as we all know, that is only possible in places where testing is available (and confirmation takes a few days) and only a fraction of people have been tested. As more testing becomes available this first metric will increase significantly. Stay healthy.

Business Intelligence 51

Business Intelligence Measurement Metrics Cost-Benefit 51

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. They can be again classified as random testing and optimization.

Data Analytics 86

Data Analytics Software Analytics Statistics 86

CIO Business Intelligence

MAY 26, 2022

Expectedly, advances in artificial intelligence (AI), machine learning (ML), and predictive modeling are giving enterprises – as well as small/medium-sized businesses – a never-before opportunity to automate their recruitment even as they deal with radical changes in workplace practices involving remote and hybrid work.

Advertising 128

Advertising Machine Learning Software Measurement 128

IBM Big Data Hub

JUNE 29, 2023

First, availability measures the operational capacity of an asset over time. While reliability and availability are both measured in percentages, it’s possible—even likely—that these percentages will differ even when referring to the same piece of equipment.

Cost-Benefit 88

Cost-Benefit Measurement Management Predictive Analytics 88

CIO Business Intelligence

MAY 28, 2022

Expectedly, advances in artificial intelligence (AI), machine learning (ML), and predictive modeling are giving enterprises – as well as small/medium-sized businesses – a never-before opportunity to automate their recruitment even as they deal with radical changes in workplace practices involving remote and hybrid work.

Advertising 119

Advertising Machine Learning Software Measurement 119

DataRobot Blog

JUNE 23, 2022

Human intuition is relied on, or an older, hand-build BI/predictive model exists, or perhaps a set of heuristics were documented that more or less predict something. Go Beyond Predictions. Far fewer AI models succeed in creating business value when there is no existing prediction to replace. Learn More.

Predictive Modeling 59

Predictive Modeling Modeling Data Science Measurement 59

DataRobot

NOVEMBER 29, 2021

We’ll focus on evaluating a model for biased behavior, which can occur during the training process or after it has been deployed in a production environment. . A model is biased when it predicts different outcomes for features in the training dataset. As with model accuracy, there are many metrics one can use to measure bias.

Technology 52

Technology Metrics Predictive Modeling Modeling 52

Business Over Broadway

SEPTEMBER 27, 2018

In this paper, I show you how marketers can improve their customer retention efforts by 1) integrating disparate data silos and 2) employing machine learning predictive analytics. Your marketing strategy is only as good as your ability to deliver measurable results. genetic counseling, genetic testing).

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

DataKitchen

SEPTEMBER 21, 2023

In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets. Running these automated tests as part of your DataOps and Data Observability strategy allows for early detection of discrepancies or errors.

Testing 176

Testing Data Quality Predictive Modeling Metrics 176

Smarten

JUNE 29, 2018

Business Problem: An ecommerce company wants to measure the impact of product price, product promotions, and holiday seasonality on product sales. Business Problem: An agriculture production firm wants to predict the impact of the amount of rainfall, humidity, and temperature on the yield of particular crop. Use Case – 1.

Business Analysis 40

Business Analysis IT Sales Statistics 40

Smarten

JUNE 29, 2018

Correlation is a statistical measure that indicates the extent to which two variables fluctuate together A positive correlation indicates the extent to which those variables increase or decrease in parallel. The Spearman’s Rank Correlation is a measure of correlation between two ranked (ordered) variables. About Smarten.

Business Analysis 40

Business Analysis IT Measurement Statistics 40

Smarten

JUNE 29, 2018

Correlation is a statistical measure that indicates the extent to which two variables fluctuate together. The Karl Pearson’s correlation measures the degree of linear relationship between two variables. A positive correlation indicates the extent to which those variables increase or decrease in parallel.

Enterprise 40

Enterprise IT Statistics Business Intelligence 40

Birst BI

OCTOBER 30, 2018

The credit scores generated by the predictive model are then used to approve or deny credit cards or loans to customers. A well-designed credit scoring algorithm will properly predict both the low- and high-risk customers. Integrate the data sources of the various behavioral attributes into a functional data model.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

DataRobot Blog

JULY 22, 2022

Using AI-based models increases your organization’s revenue, improves operational efficiency, and enhances client relationships. You need to know where your deployed models are, what they do, the data they use, the results they produce, and who relies upon their results. That requires a good model governance framework.

Modeling 105

Modeling Risk Management Testing Risk 105

Smarten

JUNE 29, 2018

Business Problem: An eCommerce company wants to measure the impact of product price on product sales. The Smarten approach to business intelligence and business analytics focuses on the business user and provides Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist.

Enterprise 40

Enterprise Sales Statistics Business Intelligence 40

Smarten

JUNE 26, 2018

Logistic regression measures the relationship between the categorical target variable and one or more independent variables It deals with situations in which the outcome for a target variable can have two or more possible types. What is the Multinomial-Logistic Regression Classification Algorithm?

IT 40

IT Business Intelligence Predictive Modeling Statistics 40

Smarten

JUNE 29, 2018

Logistic regression measures the relationship between the categorical target variable and one or more independent variables. In this article, we will discuss the Binary Logistic Regression Classification method of analysis, and how it can be used in business. What is Binary Logistic Regression Classification?

IT 40

IT Business Intelligence Predictive Modeling Statistics 40

Insight

AUGUST 5, 2020

This created a summary features matrix of 7472 recordings x 176 summary features, which was used for training emotion label prediction models. Prediction models An Exploratory Data Analysis showed improved performance was dependent on gender and emotion. up to 20% for prediction of ‘happy’ in females?

Predictive Modeling 98

Predictive Modeling Statistics Modeling Measurement 98

Domino Data Lab

NOVEMBER 17, 2020

High throughput screening technologies have been developed to measure all the molecules of interest in a sample in a single experiment (e.g., Predictive models fit to noise approach 100% accuracy. For example, it’s impossible to know if your predictive model is accurate because it is fitting important variables or noise.

Statistics 131

Statistics Measurement Testing Predictive Modeling 131

O'Reilly on Data

SEPTEMBER 15, 2020

In my book, I introduce the Technical Maturity Model: I define technical maturity as a combination of three factors at a given point of time. Technical sophistication: Sophistication measures a team’s ability to use advanced tools and techniques (e.g., PyTorch, TensorFlow, reinforcement learning, self-supervised learning).

Cost-Benefit 293

Cost-Benefit Advertising ROI Machine Learning 293

Cloudera

SEPTEMBER 7, 2023

With the emergence of new creative AI algorithms like large language models (LLM) fromOpenAI’s ChatGPT, Google’s Bard, Meta’s LLaMa, and Bloomberg’s BloombergGPT—awareness, interest and adoption of AI use cases across industries is at an all time high. But these measures alone may not be sufficient to protect proprietary information.

Insurance 80

Insurance Risk Data-driven Finance 80

CIO Business Intelligence

AUGUST 15, 2023

Shamim Mohammad, CIO, CarMax CarMax That volume created a Sisyphean task for the company’s content writers, as they struggled to provide up-to-date information by make, model, and year for each vehicle in the company’s constantly changing inventory. They turned to artificial intelligence to help.

IT 98

IT Manufacturing IoT Cost-Benefit 98

CIO Business Intelligence

MARCH 22, 2023

Enter the new class ML data scientists require large quantities of data to train machine learning models. Then the trained models become consumers of vast amounts of data to gain insights to inform business decisions. In the training phase, the primary objective is to use existing examples to train a model.

Machine Learning 106

Machine Learning Cost-Benefit Modeling Risk 106

Alation

APRIL 14, 2022

And, as organizations progress and grow, “data drift” starts to impact data usage, models, and your business. Automatic sampling to test transformation. They strove to ramp up skills in all manner of predictive modeling, machine learning, AI, or even deep learning. Model Drift. Visual Profiling. Scheduling.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Insight

FEBRUARY 19, 2020

Arthur de Vany’s Hollywood Economics and Kaggle’s recent box office prediction challenge ) and current attempts are using increasingly sophisticated techniques. I held out 20% of this as a test set and used the remainder for training and validation. I came up with three: actor starpower , director starpower , and genre uniqueness.

Risk 67

Risk ROI Modeling Metrics 67

Domino Data Lab

AUGUST 20, 2019

Feature engineering is useful for data scientists when assessing tradeoff decisions regarding the impact of their ML models. It is a framework for approaching ML as well as providing techniques for extracting features from raw data that can be used within the models. We can also modify the features before we start the modeling process.

Testing 68

Testing Modeling Interactive Measurement 68