<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0"><channel><title><![CDATA[RSS Feed]]></title><description><![CDATA[RSS Feed]]></description><link>http://direct.ecency.com</link><image><url>http://direct.ecency.com/logo512.png</url><title>RSS Feed</title><link>http://direct.ecency.com</link></image><generator>RSS for Node</generator><lastBuildDate>Fri, 17 Apr 2026 18:30:03 GMT</lastBuildDate><atom:link href="http://direct.ecency.com/created/time-series/rss.xml" rel="self" type="application/rss+xml"/><item><title><![CDATA[Scenario Planning vs. Time-series Forecasting]]></title><description><![CDATA[When discussing ways to prepare a business or organization for future events, there are many types of projection methods that can be employed. Scenario planning and time-series forecasting are two approaches]]></description><link>http://direct.ecency.com/scenario/@chris-bates/scenario-planning-vs-time-series-forecasting</link><guid isPermaLink="true">http://direct.ecency.com/scenario/@chris-bates/scenario-planning-vs-time-series-forecasting</guid><category><![CDATA[scenario]]></category><dc:creator><![CDATA[chris-bates]]></dc:creator><pubDate>Sat, 14 Dec 2019 03:41:27 GMT</pubDate><enclosure url="https://images.ecency.com/p/RGgukq5E6HBTMBcjijyS1imqCAk7EGy61jZ1FniTP4H71zvdMVQWzfW2QyaUHkDeoxytTVfs9TYvKbt3YXSgqDPvyKWXkBTXDun8g5q2T7rLBM3JYYy4w6tc1DJzGBG?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Technical analysis library to financial datasets with pandas (python)]]></title><description><![CDATA[During the last months at Lecrin Technologies, we have been studying some financial time series such as predict bitcoin price or different challenges proposed by Numer.ai, Two Sigma Investment or G-Research.]]></description><link>http://direct.ecency.com/machine-learning/@dariolp/technical-analysis-library-to-financial-datasets-with-pandas-python</link><guid isPermaLink="true">http://direct.ecency.com/machine-learning/@dariolp/technical-analysis-library-to-financial-datasets-with-pandas-python</guid><category><![CDATA[machine-learning]]></category><dc:creator><![CDATA[dariolp]]></dc:creator><pubDate>Wed, 11 Apr 2018 10:48:03 GMT</pubDate><enclosure url="https://images.ecency.com/p/2923mN3pnd7PrxqAS8My84z8QnDpEsSBnKFsBYXvnbGZhDgvcVB23KHptD1ecAQutLFseHMeYoZxUwjR6az9GT5YNATb5NxNGVB5Yq3hNJQwTc?format=match&amp;mode=fit" length="0" type="false"/></item></channel></rss>