<?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>https://ecency.com</link><image><url>https://ecency.com/logo512.png</url><title>RSS Feed</title><link>https://ecency.com</link></image><generator>RSS for Node</generator><lastBuildDate>Tue, 14 Jul 2026 18:08:58 GMT</lastBuildDate><atom:link href="https://ecency.com/@niki196/rss" rel="self" type="application/rss+xml"/><item><title><![CDATA[Tensorflow Vs Pytorch: 3 weeks summary]]></title><description><![CDATA[TensorFlow is developed by Google Brain and actively used at Google both for research and production needs. PyTorch is a cousin of lua-based Torch framework which is actively used at Facebook. PyTorch]]></description><link>https://ecency.com/@niki196/tensorflow-vs-pytorch-3-weeks-summary</link><guid isPermaLink="true">https://ecency.com/@niki196/tensorflow-vs-pytorch-3-weeks-summary</guid><category><![CDATA[tensorflow]]></category><dc:creator><![CDATA[niki196]]></dc:creator><pubDate>Tue, 20 Feb 2018 04:43:06 GMT</pubDate></item><item><title><![CDATA[Basics of ML and DL]]></title><description><![CDATA[If you are already familiar with the basics of DL and Machine Learning (ML), you can skip directly this entire post. But if you are new to this field, then the first few paragraphs are meant for you. As]]></description><link>https://ecency.com/@niki196/basics-of-ml-and-dl</link><guid isPermaLink="true">https://ecency.com/@niki196/basics-of-ml-and-dl</guid><category><![CDATA[machinelearning]]></category><dc:creator><![CDATA[niki196]]></dc:creator><pubDate>Tue, 20 Feb 2018 04:34:30 GMT</pubDate></item><item><title><![CDATA[Algorithm storage and computation]]></title><description><![CDATA[There are 4 things to keep in mind when choosing or designing an algorithm for matrix computations:   Memory Use Speed Accuracy Scalability/Parallelization Often there will be trade-offs between these]]></description><link>https://ecency.com/@niki196/algorithm-storage-and-computation</link><guid isPermaLink="true">https://ecency.com/@niki196/algorithm-storage-and-computation</guid><category><![CDATA[datascience]]></category><dc:creator><![CDATA[niki196]]></dc:creator><pubDate>Tue, 23 Jan 2018 03:15:27 GMT</pubDate></item><item><title><![CDATA[How to make a computer to understand human language..hmm..???]]></title><description><![CDATA[You possibly guess it right – TEXT processing. How do we make computers to perform clustering, classification etc. on a text data since we know that they are generally inefficient at handling and processing]]></description><link>https://ecency.com/@niki196/5i1axb-how-to-make-a-computer-to-understand-human-language-hmm</link><guid isPermaLink="true">https://ecency.com/@niki196/5i1axb-how-to-make-a-computer-to-understand-human-language-hmm</guid><category><![CDATA[machinelearning]]></category><dc:creator><![CDATA[niki196]]></dc:creator><pubDate>Tue, 23 Jan 2018 03:05:00 GMT</pubDate></item><item><title><![CDATA[Machine Learning Humor]]></title><description><![CDATA[There are two types of people First outliers : They are an inspiration Second sampling errors : They need to be regularized.]]></description><link>https://ecency.com/@niki196/machine-learning-humor</link><guid isPermaLink="true">https://ecency.com/@niki196/machine-learning-humor</guid><category><![CDATA[life]]></category><dc:creator><![CDATA[niki196]]></dc:creator><pubDate>Wed, 20 Dec 2017 11:18:09 GMT</pubDate><enclosure url="https://i.ecency.com/p/6VvuHGsoU2QD2aHbJiivbVZV6nAA4BJrX2xi1YbtzCk7JgDosX84fjvJc4HEksGM7Ewuf2s2xBh6FK7nKBactWxvV3qAURBb5wr9CYLmJNqsoaGMVm2zYmZgV1bTAe?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Feature Engineering]]></title><description><![CDATA[“Feature engineering is another topic which doesn’t seem to merit any review papers or books, or even chapters in books, but it is absolutely vital to ML success. Much of the success of machine learning]]></description><link>https://ecency.com/@niki196/feature-engineering</link><guid isPermaLink="true">https://ecency.com/@niki196/feature-engineering</guid><category><![CDATA[featureengineering]]></category><dc:creator><![CDATA[niki196]]></dc:creator><pubDate>Tue, 19 Dec 2017 12:19:57 GMT</pubDate></item><item><title><![CDATA[Inspiring nature :)]]></title><link>https://ecency.com/@niki196/inspiring-nature</link><guid isPermaLink="true">https://ecency.com/@niki196/inspiring-nature</guid><category><![CDATA[life]]></category><dc:creator><![CDATA[niki196]]></dc:creator><pubDate>Wed, 06 Dec 2017 02:37:18 GMT</pubDate><enclosure url="https://i.ecency.com/p/S5Eokt4BcQdk7EHeT1aYjzebg2hC7hkthT45e8Ka5UMvU8PGtsD8Lp9iQZfPwNypjVrgdav?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Exasperating kid!!]]></title><link>https://ecency.com/@niki196/exasperating-kid</link><guid isPermaLink="true">https://ecency.com/@niki196/exasperating-kid</guid><category><![CDATA[life]]></category><dc:creator><![CDATA[niki196]]></dc:creator><pubDate>Sun, 03 Dec 2017 16:35:18 GMT</pubDate><enclosure url="https://i.ecency.com/p/S5Eokt4BcQdk7EHeT1aYjzebg2hC7hkthT45eEPYzq4wdUvavxHSap2rKAiyJkypKK5Z4Bx?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[De-clutter your life]]></title><description><![CDATA[I've been trying to declutter my life for the past few months. Watching youtube videos on minimalism frustrated me since the individuals putting out the videos were anything but minimalistic with their]]></description><link>https://ecency.com/@niki196/de-clutter-your-life</link><guid isPermaLink="true">https://ecency.com/@niki196/de-clutter-your-life</guid><category><![CDATA[life]]></category><dc:creator><![CDATA[niki196]]></dc:creator><pubDate>Sun, 03 Dec 2017 08:16:09 GMT</pubDate><enclosure url="https://i.ecency.com/p/S5Eokt4BcQdk7EHeT1aYjzebg2hC7hkthT45dxgYz8nkr93vp48i8cpVqj81TRXoFzEPxFY?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Apparently kid, Noah Ritter.. I love him :)]]></title><link>https://ecency.com/@niki196/apparently-kid-noah-ritter-i-love-him</link><guid isPermaLink="true">https://ecency.com/@niki196/apparently-kid-noah-ritter-i-love-him</guid><category><![CDATA[life]]></category><dc:creator><![CDATA[niki196]]></dc:creator><pubDate>Sat, 02 Dec 2017 18:15:21 GMT</pubDate><enclosure url="https://i.ecency.com/p/S5Eokt4BcQdk7EHeT1aYjzebg2hC7hkthT45eFa63kEVmnz8EvndVRUYMBy5w6YQLPrTwS6?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Artificial intelligence simplified]]></title><description><![CDATA[The easiest way to think of relationship is to visualize them – idea that came first, largest one Artificial intelligence, then Machine learning – which blossomed later, and finally Deep Learning – which]]></description><link>https://ecency.com/@niki196/artificial-intelligence-simplified</link><guid isPermaLink="true">https://ecency.com/@niki196/artificial-intelligence-simplified</guid><category><![CDATA[artificialintelligence]]></category><dc:creator><![CDATA[niki196]]></dc:creator><pubDate>Fri, 01 Dec 2017 13:03:24 GMT</pubDate><enclosure url="https://i.ecency.com/p/qjrE4yyfw5pQYiuVvgYiUBP16WHGGN7UNn1BCdGde1ssuM8TqAB9AdExDEoArASviRXzSdgB5mhoUYZ4v19HJBmbb4PZdReSwj66QAdNfg5oFeCiLyo9YybU?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Data Science – Deep Learning Glossary]]></title><description><![CDATA[D: data set: A collection of examples decision boundary: The separator between classes learned by a model in a binary class or multi-class classification problems. For example, in the following image]]></description><link>https://ecency.com/@niki196/data-science-deep-learning-glossary</link><guid isPermaLink="true">https://ecency.com/@niki196/data-science-deep-learning-glossary</guid><category><![CDATA[deeplearning]]></category><dc:creator><![CDATA[niki196]]></dc:creator><pubDate>Thu, 30 Nov 2017 12:27:12 GMT</pubDate><enclosure url="https://i.ecency.com/p/3W72119s5BjWPGGUiZ9pqnZoj8JHYxCCp9dtn2QVeLPBaukH2q6pmZZtHvp9iFkFsgdqxfqwUEg84WQNKDmzPnN19eciDoP19iFh6dUBHP1nKfRCvzRyhg?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Word Embedding(Prediction based vectors)]]></title><description><![CDATA[Word2Vec- We heard this buzz word in our Data Science world very frequently. While researching Word2Vec, I came across a lot of resources of varying usefulness. So though I’d share my collection of links]]></description><link>https://ecency.com/@niki196/word-embedding-prediction-based-vectors</link><guid isPermaLink="true">https://ecency.com/@niki196/word-embedding-prediction-based-vectors</guid><category><![CDATA[word2vec]]></category><dc:creator><![CDATA[niki196]]></dc:creator><pubDate>Wed, 29 Nov 2017 18:07:30 GMT</pubDate></item><item><title><![CDATA["Staying real- is the courageous battles we fight"]]></title><description><![CDATA[E.E.Cummings Wrote- "To be nobody but yourself in a world which is doing its best, night and day, to make you everyday but yourself." Means to fight the hardest battle which any human being can]]></description><link>https://ecency.com/@niki196/staying-real-is-the-courageous-battles-we-fight</link><guid isPermaLink="true">https://ecency.com/@niki196/staying-real-is-the-courageous-battles-we-fight</guid><category><![CDATA[stayingreal]]></category><dc:creator><![CDATA[niki196]]></dc:creator><pubDate>Wed, 29 Nov 2017 00:25:18 GMT</pubDate></item><item><title><![CDATA[Shame]]></title><description><![CDATA[Shame is a thing we are all afraid to talk about.. Though We all experience shame feeling in our life.. Less we talk about shame, the more control it has over our life.. Shame is full of fears of being]]></description><link>https://ecency.com/@niki196/shame</link><guid isPermaLink="true">https://ecency.com/@niki196/shame</guid><category><![CDATA[shame]]></category><dc:creator><![CDATA[niki196]]></dc:creator><pubDate>Tue, 28 Nov 2017 17:40:54 GMT</pubDate></item><item><title><![CDATA[How to make a computer to understand human language..hmm..???]]></title><description><![CDATA[You possibly guess it right – TEXT processing. How do we make computers to perform clustering, classification etc. on a text data since we know that they are generally inefficient at handling and processing]]></description><link>https://ecency.com/@niki196/how-to-make-a-computer-to-understand-human-language-hmm</link><guid isPermaLink="true">https://ecency.com/@niki196/how-to-make-a-computer-to-understand-human-language-hmm</guid><category><![CDATA[machinelearning]]></category><dc:creator><![CDATA[niki196]]></dc:creator><pubDate>Tue, 28 Nov 2017 09:54:51 GMT</pubDate></item></channel></rss>