This applies to many tech job interviews. But here we provide specific advice for data scientists and other professionals with a similar background. More advice is being added regularly.
Here's the list:
Added by L.V. on February 29, 2016 at 8:30pm — 2 Comments
Great article by Mike Ferguson. Articles about the big data, AI, data science or IoT ecosystems are always popular. Many have been posted here (see screenshot below):
Sometimes, the keyword…
ContinueAdded by L.V. on February 22, 2016 at 11:30am — No Comments
Data Science Central shared its predictions for 2016. More predictions can be found here. In this article, we share Scott Mongeau's predictions. The full version of this (long) article can be found…
ContinueAdded by L.V. on February 22, 2016 at 11:00am — 2 Comments
Model evaluation metrics are used to assess goodness of fit between model and data, to compare different models, in the context of model selection, and to predict how predictions (associated with a specific model and data set) are expected to be accurate.
Confidence Interval. Confidence intervals are used to assess how reliable a statistical…
ContinueAdded by L.V. on February 20, 2016 at 10:00am — 2 Comments
Feature selection is one of the core topics in machine learning. In statistical science, it is called variable reduction or selection. Our scientist published a methodology to automate this process and efficiently handle la large number of features (called variables by statisticians). Click here for details.
Here, we mention an article published by Isabelle Guyon…
ContinueAdded by L.V. on February 14, 2016 at 4:00pm — No Comments
This article focuses on cases such as Facebook and protein interaction networks. The article was written by By Paul Scherer (paulmorio) and submitted as a research paper to HackCambridge. What makes this article interesting is the fact that it compares five clustering techniques for this type of problems:
Added by L.V. on February 13, 2016 at 8:00am — No Comments
Very interesting document, relatively recent (September 2015), authored by David Donoho (Statistics professor at Stanford) and posted on one of the MIT websites, here (41 pages, PDF).
Below you will find the abstract and the table of content. Interestingly, Andrew Gelman and Vincent Granville (our data scientist)…
ContinueAdded by L.V. on February 10, 2016 at 8:30am — No Comments
This article was written by Natasha Latysheva. Here we publish a short version, with references to full source code in the original article.
Our internal data scientist had a few questions and comments about the article:
Added by L.V. on February 6, 2016 at 6:00pm — 2 Comments
You did all the right things:
Added by L.V. on February 6, 2016 at 10:30am — 2 Comments
If you read our digests, you already know that each week, we publish our picture of the week. Below is a selection from the last few months. By clicking on the link associated with each image, you will find the article in which it is described, many times with details about how the image was produced. Some of these images are interactive, when viewed on the original web page.
Related…
ContinueWhat do you think about Inora, a company that advertises itself as the New Linear Regression Approach - Scalable to Big Data. Our data scientist also developed automated regression for big data, offering source code, even an Excel implementation, and comparing his results with traditional regression techniques.…
Continue
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