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

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. It just so happens that dividing people increases engagement and makes economic sense.

Internet Publishing and Broadcasting 315

Internet Publishing and Broadcasting Broadcasting Data-driven Interactive 315

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

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." bandit problems).

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. You can home in on an optimal value by specifying, say, 32 dimensions and varying this value by powers of 2. s lead may not be the optimal choice. Natural Language Processing.] Joulin, A.,

Deep Learning 111

Deep Learning Modeling Metrics Testing 111