Rita Sallam

JULY 31, 2017

Furthermore, data science modeling, which is also largely manual, requires specialist skills that are in short supply at time when insights from advanced analytics must be pervasive to fuel digital business transformation. It will transform how users interact with data, and how they consume and act on insights.

Marketing 72

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The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

TF Lattice offers semantic regularizers that can be applied to models of varying complexity, from simple Generalized Additive Models, to flexible fully interacting models called lattices, to deep models that mix in arbitrary TF and Keras layers. The drawback of GAMs is that they do not allow feature interactions.

Machine Learning 111

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Domino Data Lab

AUGUST 8, 2019

Paco Nathan ‘s latest monthly article covers Sci Foo as well as why data science leaders should rethink hiring and training priorities for their data science teams. In this episode I’ll cover themes from Sci Foo and important takeaways that data science teams should be tracking. Introduction.

Data Science 71

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Smarten

JANUARY 3, 2019

These business users have adopted business intelligence and advanced analytical tools to gather and analyze data from varied data sources and use that analysis to identify the root cause of problems, identify opportunities, solve problems and share crucial data to support business decisions.

Business Intelligence 40

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Smarten

SEPTEMBER 9, 2024

The Definition and Evolution of the Citizen Data Scientist Role The world-renowned technology research firm, Gartner, first introduced the concept of the Citizen Data Scientist in 2016. Citizen Data Scientist candidates may also be IT team members who are interested in data science.

Prescriptive Analytics 52

Prescriptive Analytics Predictive Analytics Data-driven Business Intelligence 52

Data Science 101

OCTOBER 12, 2023

The first project we did used NLP for finance contracts (this was 2016). I get to interact with really amazing people and because the signal to noise ratio is so high, they interact back. By random chance, we were looking for technical help in Finance and a research lab was looking for meaningful projects.

Finance 64

Finance Machine Learning Interactive Manufacturing 64

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

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Smarten

JUNE 15, 2022

The reason they can do this is simple: the tools provided for this purpose are designed for human interaction. Ask a question about a point in time without the need for specific dates: How many silk blouses were sold during Christmas season in 2016 vs. 2018? They know how to search for something on Google and get the results they need.

Analytics 52

Analytics ROI Data-driven Sales 52

Smarten

SEPTEMBER 9, 2024

What is a Citizen Data Scientist, What is Their Role, What are the Benefits of Citizen Data Scientists…and More! The term, ‘Citizen Data Scientist’ has been around for a number of years. In fact, the world-renowned technology research firm, Gartner, first introduced the concept in 2016.

Consulting 52

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CIO Business Intelligence

JULY 20, 2023

A few things: Tackle bias not just in your data, but also be aware it can result from how the data is interpreted, used, or interacted with by users Lean into open source tools and data science. Chet successfully took Apigee public before the company was acquired by Google in 2016. Chet earned his B.S.

Machine Learning 40

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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

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,

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Rita Sallam

JULY 22, 2016

Gartner revamped the BI and Analytics Magic Quadrant in 2016 to reflect the mainstreaming of this market disruption. Not sure about that, but Sisense is well suited for easily harmonizing, combining and modeling many different, complex and large data sets for fast interactive analysis. Answer: Better than every other vendor?

Analytics 40

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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. Interactive bokeh plot of two-dimensional word-vector data.

Deep Learning 111

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The Unofficial Google Data Science Blog

APRIL 23, 2024

However, if we experiment with both parameters at the same time we will learn something about interactions between these system parameters. Interactions between parameters in different YouTube recommendation subsystems definitely exist, but important interactions and quadratic effects seem relatively rare. 17:263-287, 2016. [10]

Experimentation 52

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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. Column "a" is an advertiser id, "b" is a web site, and "c" is the 'interaction' of columns "a" and "b". $y$ Now for the $j$th row of data we define the index of the feature "a" as $I_a(j) in {1, 2,, mbox{#advertisers} }$. hi-fly-airlines 123.com

Modeling 40

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Domino Data Lab

AUGUST 1, 2021

The need for interaction – complex decision making systems often rely on Human–Autonomy Teaming (HAT), where the outcome is produced by joint efforts of one or more humans and one or more autonomous agents. 2016) for an example of this technique (LIME). Toy example to present intuition for LIME from Ribeiro (2016).

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Insight

MARCH 18, 2019

As data scientists, machine learning engineers, and AI practitioners, we should be aware of the behaviors of the models we build and check them for biases toward certain attributes, such as race or sex. Want to advance your career in Data Science and Artificial Intelligence? Feel free to get in touch.

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