Smarten

JANUARY 3, 2019

Self-serve BI tools provide a truly intelligent solution that suggests relationships, identifies patterns, suggests visualization techniques and formats, highlights trends and patterns, and presents predictions, so the organization can promote and encourage Citizen Analysts and advance the objectives and goals of the organization.

Business Intelligence 40

Business Intelligence Statistics Interactive Data Science 40

Jen Stirrup

JUNE 20, 2020

In efficient data science, we need to take our biases off the table in order to get a true picture of the data we are looking at. Here is the Current Ratio for the past four years for PASS: Year 2019 2018 2017 2016 Quick Ratio ((Current Assets) / Current Liabilities ) 1.03 Let’s see that data for the past few years.

Metrics 104

Metrics Business Analytics Data-driven Statistics 104

Domino Data Lab

JANUARY 6, 2019

In Paco Nathan ‘s latest column, he explores the theme of “learning data science” by diving into education programs, learning materials, educational approaches, as well as perceptions about education. He is also the Co-Chair of the upcoming Data Science Leaders Summit, Rev. Learning Data Science.

Data Science 56

Data Science Machine Learning Reporting Visualization 56

The Unofficial Google Data Science Blog

MARCH 13, 2017

By MUKUND SUNDARARAJAN, ANKUR TALY, QIQI YAN Editor's note: Causal inference is central to answering questions in science, engineering and business and hence the topic has received particular attention on this blog. A note on visualization The most convenient way to inspect our feature importances (attributions) is to visualize them.

IT 68

IT Visualization Modeling Uncertainty 68

O'Reilly on Data

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena. 1 again in proposals this year.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

The Unofficial Google Data Science Blog

JULY 11, 2017

SCOTT Time series data are everywhere, but time series modeling is a fairly specialized area within statistics and data science. Introduction Time series data appear in a surprising number of applications, ranging from business, to the physical and social sciences, to health, medicine, and engineering.

Forecasting 64

Forecasting Statistics Modeling Software 64

Domino Data Lab

SEPTEMBER 25, 2019

Conducting exploratory analysis and extracting meaningful insights from data are core components of research and data science work. Time series data is commonly encountered. We see it when working with log data, financial data, transactional data, and when measuring anything in a real engineering system. . >

Forecasting 87

Forecasting Modeling Statistics Optimization 87

Insight

JUNE 10, 2019

In 2016, Uber published its Uber Elevate White Paper , setting its aspirations on providing on-demand air taxis from San Francisco to San Jose for about $130. Alexander | June 1, 2016 Training a c onvolution neural network (CNN) to spot helipads The solution I developed rests on retraining a CNN to recognize helipads in aerial images.

Breakeven 69

Breakeven Modeling Testing Marketing 69

Domino Data Lab

OCTOBER 23, 2019

Eighty percent of this problem is collecting the data and then transforming the data. The other 20 percent is ML- and data science–related tasks like finding the right model, doing EDA, and feature engineering. Gathering the Data. there is a list of data sources to extract and transform. In Figure 6.1,

Statistics 59

Statistics Machine Learning Testing Modeling 59

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

GAMs are popular among data science and machine learning applications for their simplicity and interpretability. For example, when the prediction of an example is unexpectedly large we can trace back the prediction through visualization of the final block and identify its problematic, unexpectedly large input. Pfeifer, J.,

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

The Unofficial Google Data Science Blog

APRIL 23, 2024

Figure 4: Visualization of a central composite design. 17:263-287, 2016. [10] Journal of Machine Learning Research, 17(83):1–5, 2016. [23] In a later section, we say more about what "well spread-out'' should mean for such experiments by connecting a quantitative measure of "spread'" with model variance minimization. Domahidi, E.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Domino Data Lab

MARCH 27, 2019

Special thanks to Addison-Wesley Professional for permission to excerpt the following “Manipulating data with dplyr” chapter from the book, Programming Skills for Data Science: Start Writing Code to Wrangle, Analyze, and Visualize Data with R. Data scientists spend countless hours wrangling data.

Statistics 85

Statistics Data Science Visualization IT 85

Domino Data Lab

AUGUST 22, 2019

Data scientists and researchers require an extensive array of techniques, packages, and tools to accelerate core work flow tasks including prepping, processing, and analyzing data. Utilizing NLP helps researchers and data scientists complete core tasks faster. Visualizing data using t-SNE. Joulin, A., Example 11.9

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

The Unofficial Google Data Science Blog

MARCH 31, 2016

Often our data can be stored or visualized as a table like the one shown below. arXiv preprint arXiv:1602.00047, (2016). [8] 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, $y_j$. 434 (1996): 883-904. [7] 7] Nicholas A.

Modeling 40

Modeling Statistics Advertising Testing 40

Alation

FEBRUARY 20, 2020

With the year coming to a close, many look back at the headlines that made major waves in technology and big data – from Spark to Hadoop to trends in data science – the list could go on and on. Venky Ganti, CTO & Co-Founder: Data sprawl will finally hit its threshold.

Data Warehouse 52

Data Warehouse Visualization Enterprise Data Science 52