Domino Data Lab

APRIL 21, 2021

This is to prevent any information leakage into our test set. 2f%% of the test set." 2f%% of the test set." Fraudulent transactions are 0.17% of the test set. 2f%% of the test set." Fraudulent transactions are 50.00% of the test set. Feature Engineering. 2f%% of the training set."

Statistics 69

Statistics Machine Learning Modeling Metrics 69

Domino Data Lab

MAY 8, 2019

Agile was originally about iterating fast on a code base and its unit tests, then getting results in front of stakeholders. Perhaps if machine learning were solely being used to optimize advertising or ecommerce, then Agile-ish notions could serve well enough. That may have been the case a decade ago, but those days are long gone.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

For example, consider the following simple example fitting a two-dimensional function to predict if someone will pass the bar exam based just on their GPA (grades) and LSAT (a standardized test) using the public dataset (Wightman, 1998). Curiosities and anomalies in your training and testing data become genuine and sustained loss patterns.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

Occam's Razor

FEBRUARY 22, 2010

The secret to making optimal use of CI data lies in one single realization: You must ensure you understand how the data you are analyzing is collected. It will probably be the category that will grow the most because frankly in context others look rather sub optimal. The Optimal Competitive Analysis Process. use to your benefit.

Metrics 123

Metrics Advertising Reporting Software 123

datapine

JANUARY 31, 2022

Everything is being tested, and then the campaigns that succeed get more money put into them, while the others aren’t repeated. This methodology of “test, look at the data, adjust” is at the heart and soul of business intelligence. This company was originally founded in 2009 as a black car-hailing service in San Francisco.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Domino Data Lab

AUGUST 1, 2021

After forming the X and y variables, we split the data into training and test sets. PDPs for the bicycle count prediction model (Molnar, 2009). Next, we pick a sample that we want to get an explanation for, say the first sample from our test dataset (sample id 0). random_state=seed) y_train.value_counts(). show_in_notebook().

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Domino Data Lab

JULY 9, 2019

When he retired in 2009 he had some time on his hands. or are you looking for me to help you decide on what is the optimal treatment in order to get the outcome you want?” ” And Mark said, “Yes, we’ve got a lot of data. Please help us make sense of it.” He put together this lovely collection of essays.

Data Science 112

Data Science Machine Learning Advertising Modeling 112