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Educate-Inspire-Change
Empty Suit
Definition: An amateur who's been given the power to set the goals & objectives for professionals to follow, and thinks of himself as a strong leader.Ethics
"Veritas vos liberabit"
"It's better to build something 100 people love, than something that 1M people kind-of-like" -- Brian Chesky
"Rättvisa handlar inte om lika utfall, utan om lika spelregler" -- Alice Teodorescu
“The mediocre teacher tells. The good teacher explains. The superior teacher demonstrates. The great teacher inspires.” ― William Arthur Ward
When the facts change, I change my mind. What do you do, sir?" -- John Maynard Keynes
""Don't attribute to stupidity what can be adequately explained by a contract." -- Anonymous
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“It is difficult to get a man to understand something, when his salary depends on his not understanding it.” -- Upton Sinclair
"I do not agree with what you have to say, but I'll defend to the death your right to say it." -- VoltaireSystems view
"Our organization was designed for a problem that no longer existed; we had brought an industrial age force to an information-age conflict." --Stan McChrystal- A/B Testing
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Tag Archives: Matplotlib
Tour de Ski Final climb – does age matter for performance ?
In an earlier post, I analyzed data from the Marcialonga Ski race. Marcialonga is one of the classic long distance ski races, where both elite’ as well as amateurs compete together. In fact, the vast majority of the competitors in … Continue reading
Posted in Bayes, Data Analytics, Math, Numpy, Pandas, Probability, PYMC, Python, SNA, sports, Statistics
Tagged Bayes, Matplotlib, Numpy, Probability, PYMC, Python, Scipy, sports, Statistics
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Bayesian Linear Regression with PYMC
Python, Pandas & PYMC example on Bayesian Linear Regression, adopted from Richard McElreath’s “Statistical Rethinking” class, where he uses R as modeling language instead of PYMC. Data in a csv-file describe various attributes such as weight, height, age, gender etc … Continue reading
Posted in Bayes, Data Analytics, Numpy, Pandas, Probability, PYMC, Python, Statistics
Tagged Bayes, Matplotlib, Numpy, Pandas, Probability, PYMC, Python, Statistics
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Using Bayesian Inference to predict and bet on Italian Serie A Fotball
As my old timer readers know, I’be been using Bayesian Inference to predict and bet on various sporting events, such as FIFA World Cup, and IIHF World Championships. With some success. When the Italian premier division started for about a … Continue reading
Posted in Bayes, Data Analytics, Gambling, Machine Learning, Numpy, Probability, PYMC, Python, Simulation, Statistics
Tagged Bayes, Gambling, Machine Learning, Matplotlib, Numpy, Pandas, Probability, PYMC, Python, Scipy, Simulation, sports, Statistics, Technology
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Bayesian Multi-predictor Regression – Valet2018
[Continuing my exploration of the Swedish election results, but I thought this might be of interest also for those of you not very interested in the Swedish elections, simply because the potential MatStat’s insights – thus, the text is in … Continue reading
Posted in Bayes, Big Data, Data Analytics, Data Driven Management, Numpy, Politik, Probability, PYMC, Python, Research, Society, Statistics, Sverige
Tagged Bayes, Data Analysis, Matplotlib, Numpy, Pandas, Probability, PYMC, Python, Scipy, Statistics, Val2018
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PYMC – Markov Chain Monte Carlo regression – canonical example
Posted in Bayes, Data Analytics, Numpy, Probability, PYMC, Python, Statistics
Tagged Bayes, Markov Chain Monte Carlo, Matplotlib, Numpy, Probability, PYMC, Python, Scipy, Statistics
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Val2018 Bayesian Inference – sammanfattning
Nu är ju inte den slutgiltiga rösträkningen klar, men resultatet ur ett statistiskt / matematiskt perspektiv är ändå så stabilt att jag väljer att summera mina resultat redan nu. I graferna nedan har jag använt mig av samtliga opinionsinstituts prognoser … Continue reading
Posted in Bayes, Data Analytics, Functional Stupidity, Politik, Probability, PYMC, Society, Statistics, Sverige
Tagged Bayes, Matplotlib, Numpy, Pandas, Politik, Probability, PYMC, Python, Scipy, Society, Statistics, Sverige, Val2018
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Val2018 – sista prognosen
Första grafen: Bayesian Inference över samtliga opinionsinstituts mätningar augusti-september 2018. Andra grafen: samma rådata som ovan, obearbetat. Stora skuggade stapeln för respektive parti anger valresultatet 2014. Svarta tunna staplarna är 89:e percentilen.
Posted in Bayes, Data Analytics, Numpy, Probability, PYMC, Python, Statistics, Sverige
Tagged Bayes, Matplotlib, Numpy, Probability, Python, Statistics, Sverige, Val2018
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Convolutional Neural Networks with KERAS – Image recognition
A quick test shot with KERAS, inspired by this tutorial using the MNIST dataset of more than 60000 images of hand written digits. Task at hand: correctly identify as many as possible of these 28 x 28 images, looking like … Continue reading
Posted in Big Data, Complex Systems, Data Analytics, KERAS, Machine Learning, Neural networks, Numpy, Python
Tagged AI, Data Analysis, KERAS, Machine Learning, Matplotlib, Neural networks, Numpy, Python
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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 Bayes, Data Analysis, Gambling, HOCKEY-2018, Matplotlib, Numpy, Pandas, Probability, PYMC, Python, Scipy, sports, Statistics
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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 Bayes, Data Analysis, Gambling, Matplotlib, Numpy, Pandas, Probability, PYMC, Python, Scipy, sports, Statistics
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