<?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>Wed, 13 May 2026 17:58:08 GMT</lastBuildDate><atom:link href="http://direct.ecency.com/@ralampay/rss" rel="self" type="application/rss+xml"/><item><title><![CDATA[Refactor Neural Network in C++ (Video Tutorial)]]></title><description><![CDATA[This was a long overdue video. The past videos on the neural network implementation in C++ had a lot of issues. Plus I had to use it for a project which turned out to be useful however it forced me to]]></description><link>http://direct.ecency.com/programming/@ralampay/refactor-neural-network-in-c-video-tutorial</link><guid isPermaLink="true">http://direct.ecency.com/programming/@ralampay/refactor-neural-network-in-c-video-tutorial</guid><category><![CDATA[programming]]></category><dc:creator><![CDATA[ralampay]]></dc:creator><pubDate>Sat, 13 Jan 2018 17:52:21 GMT</pubDate><enclosure url="https://images.ecency.com/p/S5Eokt4BcQdk7EHeT1aYjzebg2hC7hkthT45eNKNiKQm3N6dzxXcGbNZ8sd7XtkbiKZBFQi?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Programming a Bittrex Bot in Ruby (Part 2)]]></title><description><![CDATA[This is part 2 of creating a bittrex bot in Ruby. Key features implemented: Fetching order books Specifying a percentage gain on when to sell a certain coin Run this program on its own instead of having]]></description><link>http://direct.ecency.com/ruby/@ralampay/programming-a-bittrex-bot-in-ruby-part-2</link><guid isPermaLink="true">http://direct.ecency.com/ruby/@ralampay/programming-a-bittrex-bot-in-ruby-part-2</guid><category><![CDATA[ruby]]></category><dc:creator><![CDATA[ralampay]]></dc:creator><pubDate>Sat, 23 Dec 2017 05:37:09 GMT</pubDate><enclosure url="https://images.ecency.com/p/S5Eokt4BcQdk7EHeT1aYjzebg2hC7hkthT45dvz5YULLfvB3YMWhK9UUzZBUEqZqPMVczKQ?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Programming a Bittrex Bot with Ruby (Part 1)]]></title><description><![CDATA[This is from my devlogs channel ( where I code a bot in Ruby to automate my trading of cryptocurrencies in the Bittrex exchange. Key points: Configuring account to interact with Bittrex API Fetching values]]></description><link>http://direct.ecency.com/ruby/@ralampay/programming-a-bittrex-bot-with-ruby-part-1</link><guid isPermaLink="true">http://direct.ecency.com/ruby/@ralampay/programming-a-bittrex-bot-with-ruby-part-1</guid><category><![CDATA[ruby]]></category><dc:creator><![CDATA[ralampay]]></dc:creator><pubDate>Sat, 23 Dec 2017 05:31:21 GMT</pubDate><enclosure url="https://images.ecency.com/p/S5Eokt4BcQdk7EHeT1aYjzebg2hC7hkthT45e6j2gxTUoGNXTwuMqroUsFQei5medou5JgE?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[DHH's Response to "What Makes Rails a Framework Worth Learning in 2017"]]></title><description><![CDATA[Source: I love this response by DHH regarding web development in Rails. This was posted last January 25, 2017. And as we enter 2018, most of his points still hold true namely: Elegance of code Convention]]></description><link>http://direct.ecency.com/ruby/@ralampay/dhh-s-response-to-what-makes-rails-a-framework-worth-learning-in-2017</link><guid isPermaLink="true">http://direct.ecency.com/ruby/@ralampay/dhh-s-response-to-what-makes-rails-a-framework-worth-learning-in-2017</guid><category><![CDATA[ruby]]></category><dc:creator><![CDATA[ralampay]]></dc:creator><pubDate>Sat, 23 Dec 2017 05:20:57 GMT</pubDate><enclosure url="https://images.ecency.com/p/EfcLDDAkyqgtH9FEhD5F4X6iJgXXuMZCcNFKoqEdM3gwBLmMnrMMBPyiJkKdvrX3xbvMDWNnGWYhB3fpMoueDTR4Uv22r?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Training  a Neural Network - A Numerical Example]]></title><description><![CDATA[Abstract Neural networks are models used to approximate a discriminative function for classification in a supervised learning fashion. You have a bunch of input in the form of n-dimensional numerical vectors]]></description><link>http://direct.ecency.com/ai/@ralampay/training-a-neural-network-a-numerical-example-part-1</link><guid isPermaLink="true">http://direct.ecency.com/ai/@ralampay/training-a-neural-network-a-numerical-example-part-1</guid><category><![CDATA[ai]]></category><dc:creator><![CDATA[ralampay]]></dc:creator><pubDate>Sat, 16 Dec 2017 11:08:18 GMT</pubDate><enclosure url="https://images.ecency.com/p/HNWT6DgoBc18gvdDhGnCGY2ivLWThxgk7hV5YXVKZmZzQYXp55G15CXcBZJWSfc4gqsem2Pbe77wVEXJoZahmWCy62AD2iayA2fuPz6F8iidWRCnveeSAEwAsSE?format=match&amp;mode=fit" length="0" type="false"/></item></channel></rss>