{"id":1592,"date":"2019-01-03T21:34:15","date_gmt":"2019-01-03T21:34:15","guid":{"rendered":"http:\/\/demensdeum.com\/blog\/?p=1592"},"modified":"2024-12-16T22:32:40","modified_gmt":"2024-12-16T19:32:40","slug":"prophet","status":"publish","type":"post","link":"https:\/\/demensdeum.com\/blog\/hi\/2019\/01\/03\/prophet\/","title":{"rendered":"Float like Michelle"},"content":{"rendered":"

[Feel the power of Artificial Intelligence<\/a>]
In this article, I will tell you how to predict the future<\/strong>.<\/p>\n

\"\"<\/figure>\n

In statistics, there is a class of problems – time series analysis. Given a date and a value of a variable, you can predict the value of this variable in the future.
At first, I wanted to implement a solution to this problem on TensorFlow<\/a>, but I found the library Prophet<\/a> from Facebook<\/a>.
Prophet<\/a> allows you to make a forecast based on data (csv) containing date (ds) and variable (y) columns. You can find out how to work with it in the documentation on the official website in the section Quick Start<\/a>
As a dataset, I used the csv download from the site https:\/\/www.investing.com<\/a>, during the implementation I used R language<\/a> and Prophet API<\/a> for it. I really liked R, because its syntax simplifies working with large arrays of data, allows you to write simpler, make fewer mistakes than when working with regular languages \u200b\u200b(Python), since you would have to work with lambda expressions, and in R everything is lambda expressions.
In order not to prepare the data for processing, I used the anytime<\/a> package, which can convert strings to dates, without preliminary processing. Converting currency strings to numbers is done using the readr package.<\/a><\/p>\n

As a result, I received a forecast that Bitcoin will cost $8,400 by the end of 2019, and the dollar exchange rate will be 61 rubles. Should I believe these forecasts? Personally, I think that I shouldn’t, because you can’t use mathematical methods without understanding their essence.<\/a><\/p>\n

Sources<\/h3>\n

https:\/\/ facebook.github.io\/prophet<\/a>
https:\/\/habr.com\/company\/ods\/blog\/323730\/ <\/a>
https:\/\/www.r-project.org\/<\/a><\/p>\n

Source code<\/h3>\n

https:\/\/gitlab.com\/demensdeum\/MachineLearning\/tree\/master\/4prophet<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

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