Author Archives: swdevperestroika

About swdevperestroika

High tech industry veteran, avid hacker reluctantly transformed to mgmt consultant.

ÅF Offshore Race – S/Y Singdoy WP ETA Prediction

LAT LON COG DIST LEGTIME CUMDIST TOT_TIME TIMEDELTA 0 59.32 18.09 0 nan nan nan nan NaT 1 59.32 18.11 103 0.84 0.12 0.84 0.12 0 days 00:07:14.260800 2 59.32 18.16 83 1.45 0.21 2.30 0.33 0 days 00:19:41.160000 3 … Continue reading

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An area preserving map projection

area preserving map projection

Posted in Maritime Technology, Nautical Information Systems | Tagged | Leave a comment

Capturing NMEA sentences over WiFi using Python

In order to figure out how the NMEA-WiFi Gateway deals with clients, e.g. if it expects any “handshake” or any other communication setup protocol, I decided to write a simulator mimicing the gateway, and then using iRegatta 2 from Zifago … Continue reading

Posted in Data Analytics, Maritime Technology, Nautical Information Systems, NMEA, Numpy, performance, Python, Simulation, TCPIP | Tagged , , , , , , , , , , , , | Leave a comment

Parsing NMEA 0183 sentences in Python

My skipper has recently bought an NMEA wifi gateway, which means that the NMEA messages from the various onboard instruments on his yacht are broadcasted on the yacht’s wifi network. This makes it very easy to grab the NMEA messages, … Continue reading

Posted in Data Analytics, Maritime Technology, Nautical Information Systems, NMEA, Python | Tagged , , , , , | Leave a comment

New Theory Cracks Open the Black Box of Deep Learning | Quanta Magazine

A new idea is helping to explain the puzzling success of today’s artificial-intelligence algorithms — and might also explain how human brains learn. — Läs på http://www.quantamagazine.org/new-theory-cracks-open-the-black-box-of-deep-learning-20170921/

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Making a living as a Professional Scientific Gambler using Bayesian Inference…?

As my readers know, over the past few weeks I’ve been conducting an experiment: Applying scientific betting on the just finished Ice Hockey World Championships.  By “scientific”, I’m referring to the exclusive use of statistical and mathematical models, simulation, and … Continue reading

Posted in Bayes, Data Analytics, Data Driven Management, Finance, Gambling, HOCKEY-2018, Math, Numpy, Probability, PYMC, Python, Simulation, Statistics | Tagged , , , , , , , , , | Leave a comment

Scientific Gambling – Ice Hockey World Championships starting tomorrow

The tournament is starting tomorrow with four games. From now on, future posts on this topic on the public Facebook group Scientific Gambling on Ice Hockey World Championships 2018 only. So, I you want to continue following how my Bayesian Inference engine … Continue reading

Posted in Bayes, Big Data, Data Analytics, Data Driven Management, Gambling, HOCKEY-2018, Math, Numpy, Probability, PYMC, Python, Statistics | Tagged , , , , , , , , , , , , | Leave a comment

Scientific Gambling – “House Advantage”

In previous post we looked at how Betting Shops, Casinos etc make money, fundamentally by ‘salting’ the odds just a tiny bit in their favor. Let’s use two very simple games to illustrate how this works, tossing coins and throwing dice. … Continue reading

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Scientific Gambling – how do betting shops make money….?

Betting shops are commercial businesses, that is, they want to and must make money in order to survive. Like any other business. So take a casino as an example: they make money – in the long run – by having … Continue reading

Posted in Bayes, Data Analytics, Gambling, HOCKEY-2018, Math, Numpy, Probability, PYMC, Pystan, Python, Simulation, Statistics | Tagged , , , , , , , , , , , | Leave a comment

Scientific gambling – How to identify potentially profitable odds/plays ?

In all sports gambling, success or failure is determined by a number of factors, luck not being the least of them, since in any sport there are loads of “Unknown Unknowns“, which we could also call “Uncertainty”. And then there … Continue reading

Posted in Bayes, Data Analytics, Data Driven Management, Gambling, HOCKEY-2018, Math, Numpy, Probability, PYMC, Python, Statistics | Tagged , , , , , , , , , , , | Leave a comment