The Data Visualisation Catalogue

APRIL 4, 2019

Then in around 2016, I first started using VR hardware and from there I had two thoughts: first, that VR is going to be the most revolutionary technology of my lifetime; and second, that VR can make the process of data analysis and presentation much easier (especially in my job as an investment analyst).

Dashboards 75

Dashboards Predictive Modeling Visualization Modeling 75

Ms SQL Girl

MAY 19, 2016

As you may already know In-database Analytics (also known as Advanced Analytics) is available in SQL Server 2016. To simplify, “In-database Advanced Analytics”: you can run powerful statistical / predictive modelling (from R) inside SQL Server. Read the official definition here. Check Out SQL Latest Bits.

Visualization 45

Visualization Predictive Modeling Statistics Reporting 45

Ms SQL Girl

MAY 19, 2016

As you may already know In-database Analytics (also known as Advanced Analytics) is available in SQL Server 2016. To simplify, “In-database Advanced Analytics”: you can run powerful statistical / predictive modelling (from R) inside SQL Server. Read the official definition here. Check Out SQL Latest Bits.

Visualization 40

Visualization Predictive Modeling Statistics Reporting 40

The Unofficial Google Data Science Blog

MARCH 31, 2016

KUEHNEL, and ALI NASIRI AMINI In this post, we give a brief introduction to random effects models, and discuss some of their uses. Through simulation we illustrate issues with model fitting techniques that depend on matrix factorization. Random effects models are a useful tool for both exploratory analyses and prediction problems.

Modeling 40

Modeling Statistics Advertising Testing 40

DataRobot Blog

AUGUST 23, 2019

Using this data, we built a historical dataset containing past results, current Elo scores (both overall and surface-specific) and tournament information, then used DataRobot to determine the best model and predict the probability that a player would win a set. Andrew received his Ph.D.

Predictive Modeling 52

Predictive Modeling Marketing Analytics Modeling Data Science 52

Paul Blogs on BI

MARCH 25, 2020

Some universities and institutions have built out predictive models based on this data which are even more likely to be erroneous. On the healthcare side, back in 2016 I blogged about how BI Dashboards were helping drive healthcare data from analysis to action in the UAE.

Business Intelligence 51

Business Intelligence Measurement Metrics Cost-Benefit 51

Smarten

SEPTEMBER 9, 2024

Planning and Preparing for a Citizen Data Scientist Initiative The term, ‘Citizen Data Scientist’ has been around since 2016, when the world-renowned technology research firm, Gartner, coined the phrase. Be sure the solution you choose has all the features you need and will be easy for your users to learn and adopt.

KPI 52

KPI Consulting Business Intelligence Predictive Modeling 52

CIO Business Intelligence

APRIL 11, 2023

They have a paradigm called the “continuous learning machine,” where engineers use AI to automate their repetitive work tasks and build predictive models to help with productivity. Chet successfully took Apigee public before the company was acquired by Google in 2016. Chet earned his B.S. IT Leadership

Uncertainty 52

Uncertainty Predictive Modeling Risk Technology 52

Domino Data Lab

OCTOBER 23, 2019

This chapter will explore the numbers behind the numbers using ML and then creating an API to serve out the ML model. This means covering details like setting up your environment, deployment, and monitoring, in addition to creating models on clean data. The lower the RMSE, the better the prediction. Phrasing the Problem.

Statistics 59

Statistics Machine Learning Testing Modeling 59

Domino Data Lab

AUGUST 1, 2021

In this article we cover explainability for black-box models and show how to use different methods from the Skater framework to provide insights into the inner workings of a simple credit scoring neural network model. 2016) for an example of this technique (LIME). See Ribeiro et al.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Insight

MARCH 18, 2019

Bias in Machine Learning Algorithms (Bottom Photos Source: ProPublica ; Top Photos Source: Pexels.com) Biases in predictive modeling are a widespread issue Machine learning and AI applications are used across industries, from recommendation engines to self-driving cars and more.

Machine Learning 77

Machine Learning Predictive Modeling Modeling Metrics 77

Smarten

SEPTEMBER 9, 2024

In fact, the world-renowned technology research firm, Gartner, first introduced the concept in 2016. Gartner defines a citizen data scientist as, ‘ 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.’

Consulting 52

Consulting Cost-Benefit Data Science Business Intelligence 52