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Vincent Granville's Blog – November 2016 Archive (4)

Three Original Math and Proba Challenges, with Tutorial

This long article covers topics ranging from applied mathematics, statistics, probability, and algorithms, to computer sciences. Original, fun problems are discussed. Even thought you won't find them in textbooks or traditional data science courses, these problems do not require more than high school mathematics to explore solutions.

Content:

Simulations, percentiles and Bates distribution

  • Problem
  • Solution
  • What you have learned…
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Added by Vincent Granville on November 25, 2016 at 10:33am — No Comments

Python, Machine Learning, and Language Wars. A Highly Subjective Point of View

This is a long article written by  Sebastian Raschka. Sebastian Raschka is the author of the bestselling book “Python Machine Learning.” As a Ph.D. candidate at Michigan State University, he is developing new computational methods in the field of computational biology. Sebastian has many years of experience with coding in Python and has given several seminars on the practical applications…

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Added by Vincent Granville on November 23, 2016 at 12:30pm — No Comments

R, Python or SAS: Which one should you learn first?

Here is our selection of articles and resources featured today. Enjoy the reading!

How We Combined Different Methods to Create Advanced Time Series Prediction

Today, businesses need to be able to predict demand and trends to stay in line with any sudden market changes and economy swings. This is exactly where forecasting tools, powered by Data Science, come into play,…

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Added by Vincent Granville on November 4, 2016 at 11:30am — No Comments

How Bayesian Inference Works: Tutorial

Guest blog by Brando Rohrer. Brandon is an author and deep learning developer. He has worked as Principal Data Scientist at Microsoft, as well as for DuPont Pioneer and Sandia National Laboratories. Brandon earned a Ph.D. in Mechanical Engineering from the Massachusetts Institute of Technology.

Bayesian inference is a way to get sharper predictions from your data. It’s particularly useful when you don’t have as much data as you would like and want to juice every last…

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Added by Vincent Granville on November 2, 2016 at 5:03pm — No Comments

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