O'Reilly on Data

DECEMBER 12, 2019

Because all ML models make mistakes, everyone who cares about ML should also care about model debugging. [1] This article is meant to be a short, relatively technical primer on what model debugging is, what you should know about it, and the basics of how to debug models in practice.

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

Smarten

JUNE 20, 2018

In this article, we will focus on the identification and exploration of data patterns and the trends that data reveals. The business can use this information for forecasting and planning, and to test theories and strategies. In this article, we have reviewed and explained the types of trend and pattern analysis.

Forecasting 40

Forecasting Statistics Business Intelligence Predictive Modeling 40

Smarten

JUNE 29, 2018

This article explains the Karl Pearson Correlation method of analysis, and how it can be applied in business. Correlation is a statistical measure that indicates the extent to which two variables fluctuate together. What is the Karl Pearson Correlation Analytical Technique?

Enterprise 40

Enterprise IT Statistics Business Intelligence 40

Smarten

JUNE 29, 2018

This article describes the Simple Linear Regression method of analysis. Simple Linear Regression is a statistical technique that attempts to explore the relationship between one independent variable (X) and one dependent variable (Y). What is Simple Linear Regression?

Enterprise 40

Enterprise Sales Statistics Business Intelligence 40

Smarten

JUNE 29, 2018

This article describes the analytical technique of multiple linear regression. Multiple Linear Regression is a statistical technique that is designed to explore the relationship between two or more variables (X, and Y). What is Multiple Linear Regression Analysis?

Business Analysis 40

Business Analysis IT Sales Statistics 40

Smarten

JUNE 29, 2018

This article looks at the ARIMAX Forecasting method of analysis and how it can be used for business analysis. An Autoregressive Integrated Moving Average with Explanatory Variable (ARIMAX) model can be viewed as a multiple regression model with one or more autoregressive (AR) terms and/or one or more moving average (MA) terms.

Forecasting 40

Forecasting Enterprise IT Business Intelligence 40

Smarten

JUNE 27, 2018

This article presents a brief explanation of Outliers, and how this type of analysis is used. 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.

IT 40

IT Business Intelligence Predictive Modeling Testing 40

Smarten

JUNE 29, 2018

This article describes the Spearman’s Rank Correlation and how it is used for enterprise analysis. 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.

Business Analysis 40

Business Analysis IT Measurement Statistics 40

Smarten

JUNE 26, 2018

This article provides a brief explanation of the ARIMA method of analytical forecasting. Autoregressive Integrated Moving Average (ARIMA) predicts future values of a time series using a linear combination of its past values and a series of errors. ’ The ARIMA model is suggested for short term forecasting.

Forecasting 40

Forecasting Enterprise IT Sales 40

Smarten

JUNE 29, 2018

This article discusses the analytical technique known as Sampling and provides a brief explanation of two types of sampling analysis, and how each of these methods is applied. What is Sampling Analysis? A random sample from each of these subgroups is taken in proportion to the subgroup size relative to the population size.

Analytics 40

Analytics Statistics Business Intelligence Predictive Modeling 40

Smarten

JUNE 28, 2018

This article discusses the analytical method of Hierarchical Clustering and how it can be used within an organization for analytical purposes. All of these tools are designed for business users with average skills and require no special skills or knowledge of statistical analysis or support from IT or data scientists.

IT 40

IT Business Intelligence Predictive Modeling Risk 40

Sisense

SEPTEMBER 25, 2020

A data scientist must be skilled in many arts: math and statistics, computer science, and domain knowledge. Statistics and programming go hand in hand. Mastering statistical techniques and knowing how to implement them via a programming language are essential building blocks for advanced analytics. Linear regression.

Statistics 98

Statistics Predictive Modeling Modeling Machine Learning 98

Smarten

JUNE 29, 2018

In this article, we will discuss the Binary Logistic Regression Classification method of analysis, and how it can be used in business. All of these tools are designed for business users with average skills and require no special skills or knowledge of statistical analysis or support from IT or data scientists.

IT 40

IT Business Intelligence Predictive Modeling Statistics 40

Smarten

JUNE 26, 2018

This article provides a brief definition of the multinomial-logistic regression classification algorithm and its uses and benefits. All of these tools are designed for business users with average skills and require no special skills or knowledge of statistical analysis or support from IT or data scientists.

IT 40

IT Business Intelligence Predictive Modeling Statistics 40

Smarten

JUNE 25, 2018

This article provides a brief explanation of the KMeans Clustering algorithm. 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 IT Business Intelligence Predictive Modeling 40

Smarten

JUNE 27, 2018

This article provides a brief explanation of the SVM Classification method of analytics. 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.

Business Analytics 40

Business Analytics Analytics IT Business Intelligence 40

Smarten

JUNE 29, 2018

In this article, we will discuss the KNN Classification method of analysis. 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 Business Intelligence Predictive Modeling Statistics 40

Smarten

JUNE 29, 2018

This article will focus on the Naïve Bayes Classification method of analysis. 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 IT Business Intelligence Forecasting 40

Smarten

JUNE 27, 2018

In this article, we will discuss the Decision Tree analysis method. 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. What is Decision Tree Analysis?

IT 40

IT Business Intelligence Predictive Modeling Statistics 40

Smarten

APRIL 19, 2024

In this article, we will discuss the current state of AI in analytics, as well as the future of this burgeoning industry and how it can be applied to analytics to simplify and clarify results and to make analytics easier for businesses and business users to leverage.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

Domino Data Lab

APRIL 21, 2021

In this article, we’ll discuss the challenge organizations face around fraud detection, how machine learning can be used to identify and spot anomalies that the human eye might not catch. In contrast, the decision tree classifies observations based on attribute splits learned from the statistical properties of the training data.

Statistics 69

Statistics Machine Learning Modeling Metrics 69

Smarten

JULY 10, 2018

This article summarizes our recent article series on the definition, meaning and use of the various algorithms and analytical methods and techniques used in predictive analytics for business users, and in augmented data preparation and augmented data discovery tools. Use Case(s): Weather Forecasting, Fraud Analysis and more.

Analytics 40

Analytics Forecasting Statistics Sales 40

Domino Data Lab

OCTOBER 23, 2019

This article provides insight on the mindset, approach, and tools to consider when solving a real-world ML problem. As a result, there has been a recent explosion in individual statistics that try to measure a player’s impact. You can add a Makefile command test that will run all of your notebooks by issuing. Introduction.

Statistics 59

Statistics Machine Learning Testing Modeling 59

Smarten

JUNE 26, 2018

This article provides a brief explanation of the FP Growth technique of Frequent Pattern Mining. 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.

Business Intelligence 40

Business Intelligence Sales Predictive Modeling Statistics 40

Smarten

JUNE 29, 2018

In this article, we discuss the analytical method known as frequent pattern mining, previously known as ‘association’ What is Frequent Pattern Mining? All of these tools are designed for business users with average skills and require no special skills or knowledge of statistical analysis or support from IT or data scientists.

Business Analysis 40

Business Analysis IT Business Intelligence Sales 40

Domino Data Lab

AUGUST 20, 2019

The problem is that a new unique identifier of a test example won’t be anywhere in the tree. Feature extraction means moving from low-level features that are unsuitable for learning—practically speaking, we get poor testing results—to higher-level features which are useful for learning. Separate out a hold-out test set.

Testing 68

Testing Modeling Interactive Measurement 68

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

Smarten

JUNE 25, 2018

This article provides a brief explanation of the definition and uses of the Descriptive Statistics algorithms. What is a Descriptive Statistics? Descriptive statistics helps users to describe and understand the features of a specific dataset, by providing short summaries and a graphic depiction of the measured data.

Statistics 40

Statistics Enterprise Measurement Business Intelligence 40

Smarten

DECEMBER 5, 2022

In this article, we provide a list with links that will detail some of the many analytical techniques your business users will employ and provide examples of how these techniques can be used to solve problems and identify opportunities with clear, easy techniques and results. Paired Sample T Test. Chi Square Test.

Predictive Analytics 52

Predictive Analytics Predictive Modeling Forecasting Testing 52

Domino Data Lab

AUGUST 22, 2019

Note These three particular words are called articles , or determiners. Although it’s not perfect, [Note: These are statistical approximations, of course!] GloVe and word2vec differ in their underlying methodology: word2vec uses predictive models, while GloVe is count based. Note that the final test word in Table 11.2—ma’am—is

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

datapine

NOVEMBER 27, 2019

We detailed the benefits and costs of good or bad quality data in our previous article on data quality management , where you can read the five important pillars to follow. However, businesses today want to go further and predictive analytics is another trend to be closely monitored.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Smarten

DECEMBER 3, 2023

This article will help you gather information about the topic of augmented analytics. Augmented Analytics vs Predictive Analytics is not really a question. Maybe you just want to understand the analytics solution market better. The world renowned technology research firm, Gartner, defines augmented analytics in this way.

Key Performance Indicator 52

Key Performance Indicator Analytics IT Predictive Analytics 52

Smarten

JUNE 21, 2018

This article provides a brief explanation of the Holt-Winters Forecasting model and its application in the business environment. Time series forecasting methods are used to extract and analyze data and statistics and characterize results to more accurately predict the future based on historical data.

Forecasting 40

Forecasting Enterprise IT Predictive Modeling 40

Jet Global

MAY 1, 2023

Advanced Analytics Some apps provide a unique value proposition through the development of advanced (and often proprietary) statistical models. Advanced Analytics Provide the unique benefit of advanced (and often proprietary) statistical models in your app. They can then pinpoint areas for improvement.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52