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. To do this, go to Visual Studio > R Tools > Options.

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. To do this, go to Visual Studio > R Tools > Options.

Visualization 40

Visualization Predictive Modeling Statistics Reporting 40

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

O'Reilly on Data

SEPTEMBER 11, 2019

Our call for speakers for Strata NY 2019 solicited contributions on the themes of data science and ML; data engineering and architecture; streaming and the Internet of Things (IoT); business analytics and data visualization; and automation, security, and data privacy. An ML-related topic, “models,” was No. This year, AI sits at No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

Domino Data Lab

OCTOBER 23, 2019

Knowing that the ultimate goal is to compare the social-media influence and power of NBA players, a great place to start is with the roster of the NBA players in the 2016–2017 season. A further diagnostic step is to plot the predicted values of the linear regression versus the actual values. ggtitle("NBA Teams 2016-2017 Faceted Plot").

Statistics 59

Statistics Machine Learning Testing Modeling 59

The Unofficial Google Data Science Blog

MARCH 31, 2016

Random Effect Models We will start by describing a Gaussian regression model with known residual variance $sigma_j^2$ of the $j$th training record's response, $y_j$. Often our data can be stored or visualized as a table like the one shown below. arXiv preprint arXiv:1602.00047, (2016). [8] 434 (1996): 883-904. [7]

Modeling 40

Modeling Statistics Advertising Testing 40

Domino Data Lab

AUGUST 1, 2021

Model distillation – this approach builds a separate explainable model that mimics the input-output behaviour of the deep network. Because this separate model is essentially a white-box, it can be used for extraction of rules that explain the decisions behind the ANN. 2016) for an example of this technique (LIME).

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139