It goes without saying that analytics is a data-driven method that has existed with a history of being misunderstood since the beginning of its introduction to the world.
Parent Company of Anytime Fitness, The Bar Method, Waxing The City, and Basecamp Fitness Taps San Diego-Based Company to Drive Growth on a Local Level
Self Esteem Brands announces it has appointed SOCi, Inc. as its new global platform of record for localized social marketing.
In my previous post about generative adversarial networks, I went over a simple method to training a network that could generate realistic-looking images.
However, there were a couple of downsides to using a plain GAN.
First, the images are generated off some arbitrary noise.
Every survival analysis method I’ve talked about so far in this series has had one thing in common: we’ve only looked at one event in a customer lifetime (churn). In many cases, that’s a perfectly fine way to go about things… we want our customers to stick with us, so churn is the event of interest.Read Full Story
Recently we added another method for kernel approximation, the Nyström method, to scikit-learn, which will be featured in the upcoming 0.13 release.Kernel-approximations were my first somewhat bigger contribution to scikit-learn and I have been thinking about them for a while.To dive into kernel approximations, first recall the kernel-trick.Read Full Story
We’ve developed a method to assess whether a neural network classifier can reliably defend against adversarial attacks not seen during training. Our method yields a new metric, UAR (Unforeseen Attack Robustness), which evaluates the robustness of a single model against an unanticipated attack, and highlights the need to measure performance across a more diverse range of unforeseen attacks.Read Full Story
In Pandas, one can easily apply operations on all the data using the apply method. However, this method is quite slow and is not useful when scaling up your methods. Is there a way to speed up these operations? And if so, how? Yes, there is! This blog post will explain how you can use […]
The post Scale out your Pandas DataFrame operations using Dask appeared first on Data Blogger.
Back in 2005, I came up with a method to try to estimate how lucky a player was in a given season (see my article in BRJ 34, here). I compared his performance to a weighted average of his two previous seasons and his two subsequent seasons, and attributed the difference to luck.Read Full Story