Birst BI

OCTOBER 30, 2018

The foundation of predictive analytics is based on probabilities. To generate accurate probabilities of future behavior, predictive analytics combine historical data from any number of applications with statistical algorithms. A well-designed credit scoring algorithm will properly predict both the low- and high-risk customers.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

Insight

AUGUST 5, 2020

While most of these signals are implicitly communicated during human-to-human interaction, we do not have a method for quantifying feeling and mood through individual behavioral signals expressed on the digital platform. Summary statistics (i.e. Improvements in AUC values across models were also accompanied by increased precision?

Predictive Modeling 98

Predictive Modeling Statistics Modeling Measurement 98

Domino Data Lab

NOVEMBER 17, 2020

Classical statistics, developed in the 20 th century for small datasets, do not work for data where the number of variables is much larger than the number of samples (Large P Small N, Curse of Dimensionality, or P >> N data). Predictive models fit to noise approach 100% accuracy. Antimicrobial. Autoimmunity. IL-4, IL-13.

Statistics 131

Statistics Measurement Testing Predictive Modeling 131

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

Domino Data Lab

OCTOBER 23, 2019

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. test: py.test --nbval notebooks/*.ipynb. 05) in predicting changes in attendance. The lower the RMSE, the better the prediction.

Statistics 59

Statistics Machine Learning Testing Modeling 59

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

The Unofficial Google Data Science Blog

MARCH 31, 2016

Finally, through a case study of a real-world prediction problem, we also argue that Random Effect models should be considered alongside penalized GLM's even for pure prediction problems. Random effects models are a useful tool for both exploratory analyses and prediction problems. hi-fly-airlines 123.com

Modeling 40

Modeling Statistics Advertising Testing 40

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

Domino Data Lab

AUGUST 22, 2019

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: A test set of 19,500 such analogies was developed by Tomas Mikolov and his colleagues in their 2013 word2vec paper.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

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

JULY 26, 2022

“Users can analyze and interact with data with full visibility of dashboards, reports and other BI objects.” The Smarten Augmented Analytics and BI platform allows business users to leverage deep dive analysis using highly interactive dashboards, reports and NLP search on a mobile device.

Key Performance Indicator 74

Key Performance Indicator Analytics Business Intelligence Dashboards 74

datapine

NOVEMBER 27, 2019

Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. 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.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

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. HoloClean performs this automatically in a principled, statistical manner.

Machine Learning 347

Machine Learning Statistics Data Quality Modeling 347

Smarten

DECEMBER 3, 2023

As Springboard notes, ‘Augmented Analytics is an example of human machine interaction in the data science field.’ Augmented Analytics vs Predictive Analytics is not really a question. The augmented analytics solution is typically supported by natural language processing (NLP) to support users in the query and results process.

Key Performance Indicator 52

Key Performance Indicator Analytics IT Predictive Analytics 52

Jet Global

MAY 1, 2023

As rich, data-driven user experiences are increasingly intertwined with our daily lives, end users are demanding new standards for how they interact with their business data. Embedded Analytics Drive Successful Consumer Applications Consumer web applications have transformed how people use and interact with data.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52