O'Reilly on Data

DECEMBER 12, 2019

Model debugging is an emergent discipline focused on finding and fixing problems in ML systems. In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. Interpretable ML models and explainable ML. 9] See: Teach/Me Data Analysis. [10]

Machine Learning 273

Machine Learning Modeling Testing Risk Management 273

Rocket-Powered Data Science

SEPTEMBER 20, 2021

The data science team may be focused on feature importance metrics, feature engineering, predictive modeling, model explainability, and model monitoring. That’s enterprise-wide agile curiosity, question-asking, hypothesizing, testing/experimenting, and continuous learning. That’s data democratization.

Data Science 286

Data Science Forecasting Business Intelligence Sales 286

O'Reilly on Data

MARCH 24, 2020

For example, a pre-existing correlation pulled from an organization’s database should be tested in a new experiment and not assumed to imply causation [3] , instead of this commonly encountered pattern in tech: A large fraction of users that do X do Z. In particular, determining causation from correlation can be difficult.

Machine Learning 363

Machine Learning Statistics Data Quality Data Collection 363

O'Reilly on Data

SEPTEMBER 15, 2020

With well-formed goals, data scientists and machine learning engineers can then apply the scientific method to test different approaches in order to determine the validity of the hypothesis, and assess whether a given approach is feasible and can achieve the goal. automated retirement portfolio rebalancing and maximized ROI).

Advertising 359

Advertising Cost-Benefit ROI Machine Learning 359

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

CIO Business Intelligence

JANUARY 19, 2024

The exam tests general knowledge of the platform and applies to multiple roles, including administrator, developer, data analyst, data engineer, data scientist, and system architect. Candidates for the exam are tested on ML, AI solutions, NLP, computer vision, and predictive analytics.

Data Science 126

Data Science Machine Learning Predictive Modeling Forecasting 126

CIO Business Intelligence

JULY 5, 2022

Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more. Business analytics also involves data mining, statistical analysis, predictive modeling, and the like, but is focused on driving better business decisions.

Business Analytics 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

Cloudera

DECEMBER 4, 2024

To unlock the full potential of AI, however, businesses need to deploy models and AI applications at scale, in real-time, and with low latency and high throughput. The emergence of GenAI, sparked by the release of ChatGPT, has facilitated the broad availability of high-quality, open-source large language models (LLMs).

Metrics 73

Metrics Data Processing Machine Learning Deep Learning 73

CIO Business Intelligence

JUNE 14, 2023

Organization: AWS Price: US$300 How to prepare: Amazon offers free exam guides, sample questions, practice tests, and digital training. The exam tests general knowledge of the platform and applies to multiple roles, including administrator, developer, data analyst, data engineer, data scientist, and system architect.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

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

Smart Data Collective

MARCH 23, 2022

Software that has bugs need to be properly tested at all stages of development for both functionalities as well as cybersecurity. The industry has also shown that the automation of software testing and especially cyber security testing, results in systems that are more reliable and safer.

Internet of Things 131

Internet of Things IoT Cost-Benefit Testing 131

Domino Data Lab

OCTOBER 7, 2020

MANOVA, for example, can test if the heights and weights in boys and girls is different. This statistical test is correct because the data are (presumably) bivariate normal. In high dimensions the data assumptions needed for statistical testing are not met. The accuracy of any predictive model approaches 100%.

Statistics 145

Statistics Testing Predictive Modeling Big Data 145

DataRobot Blog

JULY 22, 2022

That requires a good model governance framework. At many organizations, the current framework focuses on the validation and testing of new models, but risk managers and regulators are coming to realize that what happens after model deployment is at least as important. Legacy Models. Future Models.

Modeling 105

Modeling Risk Management Testing Machine Learning 105

Cloudera

OCTOBER 14, 2020

Many companies build machine learning models using libraries, whether they are building perception layers for autonomous vehicles, allowing autonomous vehicle operation, or modeling a complex jet engine. Step 1: Using the training data to create a model/classifier. Fig 1: Turbofan jet engine.

Machine Learning 97

Machine Learning Modeling Cost-Benefit Testing 97

Domino Data Lab

NOVEMBER 17, 2020

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. As we are still left with a Large P Small N problem, direct hypothesis testing is not possible. The 12 are listed in Table 1.

Statistics 131

Statistics Measurement Testing Predictive Modeling 131

datapine

JANUARY 31, 2022

Everything is being tested, and then the campaigns that succeed get more money put into them, while the others aren’t repeated. This methodology of “test, look at the data, adjust” is at the heart and soul of business intelligence. Your Chance: Want to try a professional BI analytics software?

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Smart Data Collective

SEPTEMBER 17, 2020

Financial institutions such as banks have to adhere to such a practice, especially when laying the foundation for back-test trading strategies. Big Data can efficiently enhance the ways firms utilize predictive models in the risk management discipline. The Role of Big Data.

Big Data 145

Big Data Finance Risk Management Risk 145

Smarten

SEPTEMBER 30, 2024

Knowledgebase Articles Datasets & Cubes : Spark Sql : Split the dataset columns using Regex Dashboards Improve dashboard loading performance for dashboards with multiple objects Integration API : API Call to rebuild cubes / datasets Predictive Use cases Assisted predictive modelling : Classification : Machine Maintenance Using Smarten Assisted (..)

Predictive Modeling 69

Predictive Modeling Dashboards Sales Visualization 69

DataKitchen

JUNE 19, 2023

Using automated data validation tests, you can ensure that the data stored within your systems is accurate, complete, consistent, and relevant to the problem at hand. The image above shows an example ‘’data at rest’ test result. For example, a test can check the top fifty customers or suppliers. What is the acceptable range?

Testing 100

Testing Data Quality Cost-Benefit Metrics 100

Smarten

JULY 30, 2024

Assisted Predictive Modeling Enables Business Users to Predict Results with Easy-to-Use Tools! Gartner predicted that, ‘75% of organizations will have deployed multiple data hubs to drive mission-critical data and analytics sharing and governance.’

Predictive Analytics 64

Predictive Analytics Prescriptive Analytics Predictive Modeling Analytics 64

CIO Business Intelligence

JUNE 7, 2022

Predictive analytics is often considered a type of “advanced analytics,” and frequently depends on machine learning and/or deep learning. Prescriptive analytics is a type of advanced analytics that involves the application of testing and other techniques to recommend specific solutions that will deliver desired outcomes.

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

Smarten

MAY 9, 2022

Predictive Use cases. Independent Sample T-test Using Smarten Augmented Analytics. Customer Churn model using Smarten Assisted Predictive Modelling. LDAP/AD : AD Integration in Smarten. Embedded / API Integration : API Call to rebuild cubes / datasets. Forum Topics. LDAP/AD : How to configure AD in Smarten?

Predictive Modeling 78

Predictive Modeling Dashboards Testing Modeling 78

Smarten

JUNE 30, 2023

Knowledgebase Articles SSDP : Create dataset/cube using stored procedures in RDBMS Others: Configuring SSL Certificate for Smarten Time Series : Configuration of Timeseries Year Selection in Dashboard Filters Predictive Use cases One-Way Anova test using Smarten Augmented Analytics Machine Maintenance Using Smarten Assisted Predictive Modelling Forum (..)

Predictive Modeling 78

Predictive Modeling Dashboards Publishing Testing 78

Smarten

FEBRUARY 1, 2024

Knowledgebase Articles Datasets & Cubes : Calculating Pending Completion Months for an Ongoing Project General : Publish : Working with E-mail Delivery and Publishing Task Installation : Installation on Windows : Bypassing Smarten executable files from Antivirus Scan Predictive Use cases Assisted predictive modelling : Classification : Customer (..)

Predictive Modeling 64

Predictive Modeling Publishing Testing Modeling 64

CIO Business Intelligence

JULY 24, 2023

It has also developed predictive models to detect trends, make predictions, and simulate results. We had some tests in the laboratory first, and then we tested with the fans. One of the things Bruno and her team learned through fan testing was the need to educate the audience about data. “We

Broadcasting 98

Broadcasting Recreation/Entertainment Testing Machine Learning 98

Smarten

NOVEMBER 26, 2018

Predictive Analytics used to involve a crystal ball but, today, there are other options and they are more widely accepted in the business community! And, with Assisted Predictive Modeling , your business users can leverage sophisticated tools, algorithms and techniques in a simple, intuitive environment to predict future results.

Predictive Analytics 58

Predictive Analytics Predictive Modeling Analytics Forecasting 58

DataRobot

JANUARY 20, 2022

As ICSs mature digitally, there is a need to ensure that all processes, datasets, and models are transparent and are free from bias. – The DataRobot and Snowflake platforms include extensive built-in trust features to enable explainability and end-to-end bias and fairness testing and monitoring over time. Public sector data sharing.

Data-driven 145

Data-driven Experimentation Predictive Modeling Data Warehouse 145

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 105

Data Analytics Software Analytics Statistics 105

Smarten

APRIL 1, 2024

Knowledgebase Articles Business Use Cases : Help & Manuals : Minimizing Number of Steps using Custom SQL in SSDP Geomap : Geomap types and configuration : Importing areas and their Lat / Long Installation : Installation on Windows : Bypassing Smarten executable files from Antivirus Scan Predictive Use cases Assisted predictive modelling : Hypothesis (..)

Predictive Modeling 64

Predictive Modeling Testing Modeling Analytics 64

Smarten

MAY 13, 2024

Incorporate PMML Integration Within Augmented Analytics to Easily Manage Predictive Models! PMML is Predictive Model Markup Language. It is an interchange format that provides a method by which analytical applications and software can describe and exchange predictive models. So, what is PMML Integration?

Predictive Modeling 64

Predictive Modeling Data mining Predictive Analytics Modeling 64

CIO Business Intelligence

SEPTEMBER 10, 2024

We envisioned harnessing this data through predictive models to gain valuable insights into various aspects of the industry. This included predicting political outcomes, such as potential votes on pipeline extensions, as well as operational issues like predicting the failure of downhole submersible pumps, which can be costly to repair.

IT 122

IT Risk Risk Management Predictive Modeling 122

Data Science and Beyond

SEPTEMBER 19, 2016

Some people equate predictive modelling with data science, thinking that mastering various machine learning techniques is the key that unlocks the mysteries of the field. However, there is much more to data science than the What and How of predictive modelling. Making Bayesian A/B testing more accessible.

Data Science 66

Data Science Predictive Modeling Experimentation Deep Learning 66

CIO Business Intelligence

DECEMBER 11, 2023

This can include steps like replacing the traditional net present value/discounted cash flow calculator with multi-scenario models to stress-test multiple different forecasts under countless different scenarios.

Finance 105

Finance Forecasting IoT Predictive Modeling 105

Smarten

FEBRUARY 6, 2025

Predictive Modeling A wizard-based, guided user interface (UI) helps users to create predictive models with no need for IT intervention, and no programming or scripting experience.

Predictive Analytics 40

Predictive Analytics Key Performance Indicator Analytics Predictive Modeling 40

Smarten

JULY 23, 2019

Put simply, predictive analytics is a method used to forecast and predict the future results and needs of an organization using historical data and a comprehensive set of data from across and outside the enterprise. Predictive Modeling allows users to test theories and hypotheses and develop the best strategy.

Modeling 64

Modeling Predictive Analytics Predictive Modeling IT 64

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 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. How Can the Independent Samples T Test Method Benefit an Organization? About Smarten.

Testing 40

Testing Statistics IT Business Intelligence 40