O'Reilly on Data

MARCH 23, 2021

On top of this, pre-existing societal biases are being reinforced and promulgated at previously unheard of scales as we increasingly integrate machine learning models into our daily lives. Put simply, we are reduced to the inputs of an algorithm. Footnotes.

Internet Publishing and Broadcasting 317

Internet Publishing and Broadcasting Broadcasting Data-driven Interactive 317

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 Modeling Marketing Analytics Data Science 52

CIO Business Intelligence

JUNE 22, 2022

Around 2016, we started talking about data in motion within the context of an enterprise data platform. Data in motion is one of three broad labels used to describe data as part of a unified data life cycle. It can be “at rest”, “in use”, or “in motion”. At the same time, 5G adoption accelerates the Internet of Things (IoT).

IoT 96

IoT IT Manufacturing Internet of Things 96

Cloudera

APRIL 27, 2022

Around 2016, we started talking about data in motion within the context of an enterprise data platform. Data in motion is one of three broad labels used to describe data as part of a unified data life cycle. It can be “at rest”, “in use”, or “in motion”. At the same time, 5G adoption accelerates the Internet of Things (IoT).

IoT 98

IoT IT Manufacturing Internet of Things 98

O'Reilly on Data

SEPTEMBER 11, 2019

So, we used a form of the Term Frequency-Inverse Document Frequency (TF/IDF) technique to identify and rank the top terms in this year’s Strata NY proposal topics—as well as those for 2018, 2017, and 2016. 2) is unchanged from Strata NY 2018, it’s up three places from Strata NY 2017—and eight places relative to 2016.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

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. 5 is labeled as low.

Machine Learning 77

Machine Learning Predictive Modeling Modeling Metrics 77

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

We have many routine analyses for which the sparsity pattern is closer to the nested case and lme4 scales very well; however, our prediction models tend to have input data that looks like the simulation on the right. A Scalable Blocked Gibbs Sampling Algorithm For Gaussian And Poisson Regression Models." 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

Domino Data Lab

AUGUST 22, 2019

GloVe and word2vec differ in their underlying methodology: word2vec uses predictive models, while GloVe is count based. Neural machine translation (NMT) is a quintessential class of seq2seq models, with Google Translate’s machine-translation algorithm serving as an example of NMT being used in a production system. Joulin, A.,

Deep Learning 111

Deep Learning Modeling Metrics Testing 111