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Vincent Granville's Blog – February 2017 Archive (27)

JavaScript Library for Plotting Water Data for the Nation

A new JavaScript library, called GWIS (Graphing Water Information System), can create time-series plots of information measured at U.S. Geological Survey hydrologic data collection sites across the United States.

Developed by the USGS Texas Water Science Center, the user-friendly interface integrates the open-source dygraphs JavaScript charting library with hydrologic data…

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Added by Vincent Granville on February 8, 2017 at 9:08am — No Comments

Machine Learning Summarized in One Picture

Here is a nice summary of traditional machine learning methods, from Mathworks.

I also decided to add the following picture below, as it illustrates a method that was very popular 30 years ago but that seems to have been forgotten recently: mixture of Gaussian. In the example below, it is…

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Added by Vincent Granville on February 5, 2017 at 10:00pm — 10 Comments

Weekly Digest, February 6

Monday newsletter published by Data Science Central. Previous editions can be found here.  The contribution flagged with a + is our selection for the picture of the week.

Announcement…

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Added by Vincent Granville on February 4, 2017 at 11:30am — No Comments

Plotting Multiple Columns in D3

Guest blog post by by Brian Back.

From the wide range of things you can do with D3, still one of the best things to make is the timeseries plot. In this post, I’ll walk through the basics of making a multi-column point plot/scatter plot. We’ll use a GISS dataset from NASA; dataset can be found …

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Added by Vincent Granville on February 4, 2017 at 11:00am — No Comments

Thursday News:: Deep Learning, Python, Outliers, Regression, Data Sets

Here is our selection of featured articles and resources posted since Monday.

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Added by Vincent Granville on February 2, 2017 at 10:00am — No Comments

Distribution of Arrival Times for Extreme Events

Most of the articles on extreme events are focusing on the extreme values. Very little has been written about the arrival times of these events. This article fills the gap. 

We are interested here in the distribution of arrival times of successive records in a time series, with potential applications to global warming assessment, sport analytics, or high frequency trading. The purpose here is to discover what the distribution of these arrival times is, in absence of any…

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Added by Vincent Granville on February 1, 2017 at 7:30pm — 2 Comments

Data Science in Python: Pandas Cheat Sheet

This cheat sheet, along with explanations, was first published on DataCamp. Click on the picture to zoom in. To view other cheat sheets (Python, R, Machine Learning, Probability, Visualizations, Deep Learning, Data Science, and so on) click here

To view a…

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Added by Vincent Granville on February 1, 2017 at 11:00am — 1 Comment

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