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Posted on January 11, 2018 at 2:30pm 0 Comments 0 Likes
Posted on January 5, 2018 at 12:30pm 0 Comments 5 Likes
This article was written by Blaine Bateman
In this post, I will demonstrate the use of nonlinear models for time series analysis, and contrast to linear models. I will use a (simulated) noisy and nonlinear time series of sales data, use multiple linear regression and a small neural network to fit training data, then predict 90 days forward. I implemented all of this in R, although it could be done in a number of…
ContinuePosted on December 31, 2017 at 12:00pm 0 Comments 0 Likes
This article is by Nikolay Laptev, Slawek Smyl, and Santhosh Shanmugam.
At Uber, event forecasting enables us to future-proof our services based on anticipated user demand. The goal is to accurately predict where, when, and how many ride requests Uber will receive at any given time.
Extreme events—peak travel times such as holidays, concerts, inclement weather,…
ContinuePosted on December 23, 2017 at 12:00pm 0 Comments 0 Likes
This article is written by Giuseppe Bonaccorso.
One of the most interesting effects of PCA (Principal Component Analysis) is to decorrelate the input covariance matrix C, by computing the eigenvectors and operating a base change using a matrix V:…
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