В работе

Build a Bayesian inference in Python to predict colours

I need a bayesian inference, using Markov Chain or Monte Carlo, in Python, to predict the next boxes colours based on past colours.

The past data has the following data:

Index, Begin timestamp, End timestamp, Box colour


1, 2019/05/14 15:10, 2019/05/14 16:35, Blue

2, 2019/05/14 16:35, 2019/05/14 17:01, Blue

3, 2019/05/14 17:01, 2019/05/14 19:50, Blue

4, 2019/05/14 19:50, 2019/05/14 21:00, Red

The program must be able to calculate the probabilities for next box and subsequents being blue or red:

- Next boxes

- Next 2 boxes

- Next 3 boxes

- and so on until 10 boxes

Must be easy to use as I´ll put the past N boxes and it must predicts the next boxes.

The final product for this project must be:

1 - The Python source code

2 - Final calculations (functions or parameters) that can be implemented in another programming language. The others languages doesn´t have library for bayesian calculations. So, maybe an algorithm can be generated to be implemented.

There is an example attached: boxcolors.csv.

The begin and end timestamps are in format DD/MM/YYYY HH:MM

Квалификация: Python, Machine Learning (ML)

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О работодателе:
( 3 отзыв(-а, -ов) ) Goiânia, Brazil

ID проекта: #20279251

24 фрилансеров(-а) в среднем готовы выполнить эту работу за $157


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