<?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, 10 Apr 2026 21:39:31 GMT</lastBuildDate><atom:link href="http://direct.ecency.com/@lesley2958/rss" rel="self" type="application/rss+xml"/><item><title><![CDATA[Naive Bayes Algorithm: Bayes Theorem (Part 1)]]></title><description><![CDATA[Setup This guide was written in Python 3.6. Python and Pip If you haven't already, please download Python and Pip. Introduction In this tutorial set, we'll review the Naive Bayes Algorithm used in the]]></description><link>http://direct.ecency.com/datascience/@lesley2958/naive-bayes-algorithm-bayes-theorem-part-1</link><guid isPermaLink="true">http://direct.ecency.com/datascience/@lesley2958/naive-bayes-algorithm-bayes-theorem-part-1</guid><category><![CDATA[datascience]]></category><dc:creator><![CDATA[lesley2958]]></dc:creator><pubDate>Thu, 17 Aug 2017 19:21:24 GMT</pubDate><enclosure url="https://images.ecency.com/p/FxX5caie56yo98JMjaLgRZCTPoFRjHAdN8rpLRTuCYB2gyugPf7ap7GcHug7GkNR13CCssfNXBqj6eFJWPAwNQKmWH3tRJg2kPQMCyLGSjQG?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Intro to Linear Regression (Part 1)]]></title><description><![CDATA[1.0 Introduction Regression Analysis is a predictive modeling technique for figuring out the relationship between a dependent and independent variable. This is used for forecasting, time series modeling,]]></description><link>http://direct.ecency.com/machinelearning/@lesley2958/intro-to-linear-regression-part-1</link><guid isPermaLink="true">http://direct.ecency.com/machinelearning/@lesley2958/intro-to-linear-regression-part-1</guid><category><![CDATA[machinelearning]]></category><dc:creator><![CDATA[lesley2958]]></dc:creator><pubDate>Thu, 17 Aug 2017 03:03:42 GMT</pubDate><enclosure url="https://images.ecency.com/p/FxX5caie56yo98JMjaLgRZCTPoFRjHAdN8rpLRTuCZdDPTunxydxNYtuvF83oaNXuDqRuUHkZsdTNDrR1E4Cnw1ZE3TaUzsoEG8Wr6Ngso4Y?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Natural Language Processing (Part 3 - WordNets & Info Extraction)]]></title><description><![CDATA[Introduction Again, continuing this tutorial series on Natural language processing, I'll introduce wordnets with the Python module, nltk. For reference, you can check out previous posts here and here.]]></description><link>http://direct.ecency.com/nlp/@lesley2958/natural-language-processing-part-3-wordnets-and-info-extraction</link><guid isPermaLink="true">http://direct.ecency.com/nlp/@lesley2958/natural-language-processing-part-3-wordnets-and-info-extraction</guid><category><![CDATA[nlp]]></category><dc:creator><![CDATA[lesley2958]]></dc:creator><pubDate>Wed, 16 Aug 2017 00:00:48 GMT</pubDate></item><item><title><![CDATA[R Programming Tutorial (Part 2 - Data Collections!)]]></title><description><![CDATA[Introduction Working off of my previous R programming post here, I'll continue with the core of R programming: data collections. Data Collections Frequently, your program will require that you store multiple]]></description><link>http://direct.ecency.com/r/@lesley2958/r-programming-tutorial-part-2-data-collections</link><guid isPermaLink="true">http://direct.ecency.com/r/@lesley2958/r-programming-tutorial-part-2-data-collections</guid><category><![CDATA[r]]></category><dc:creator><![CDATA[lesley2958]]></dc:creator><pubDate>Tue, 15 Aug 2017 18:54:21 GMT</pubDate></item><item><title><![CDATA[Linear Algebra with Python -- Vectors.]]></title><description><![CDATA[0.0 Setup This guide was written in Python 3.6. 0.1 Python and Pip Download Python and Pip. 0.2 Libraries We'll be working with numpy and scipy, so make sure to install them. Pull up your terminal and]]></description><link>http://direct.ecency.com/programming/@lesley2958/linear-algebra-with-python-vectors</link><guid isPermaLink="true">http://direct.ecency.com/programming/@lesley2958/linear-algebra-with-python-vectors</guid><category><![CDATA[programming]]></category><dc:creator><![CDATA[lesley2958]]></dc:creator><pubDate>Mon, 14 Aug 2017 17:08:27 GMT</pubDate><enclosure url="https://images.ecency.com/p/46aP2QbqUqBqsHABbnGSoRND6yXCCW93ZWZ5LWLCogSzcHv3BkSzGYFcwiSow13X8iY6qj5v2nNzw9arkUWncRosDCCU?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Data Visualization with Python -- GeoSpatial!]]></title><description><![CDATA[0.0 Setup This guide was written in Python 3.6. 0.1 Python and Pip If you haven't already, download Python and Pip. 0.2 Libraries pip3 install geojsonio pip3 install geopandas pip3 install shapely pip3]]></description><link>http://direct.ecency.com/datascience/@lesley2958/data-visualization-with-python-geospatial</link><guid isPermaLink="true">http://direct.ecency.com/datascience/@lesley2958/data-visualization-with-python-geospatial</guid><category><![CDATA[datascience]]></category><dc:creator><![CDATA[lesley2958]]></dc:creator><pubDate>Sun, 13 Aug 2017 16:32:39 GMT</pubDate><enclosure url="https://images.ecency.com/p/7DceLgR4szFxUaF6f272aiLm26N7BouyCGuf1ZxbQ2x5q9xXWqQEsQcb1ghA1fVbQY6vhMufw9qTVxVtfVvuC?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Machine Learning Series (Support Vector Machines)]]></title><description><![CDATA[Introduction In this series of posts, I'll introduce the theory behind Support Vector Machines, a class of machine learning algorithms used for classification purposes. 1.0 Support Vector Machines Support]]></description><link>http://direct.ecency.com/machinelearning/@lesley2958/machine-learning-series-support-vector-machines</link><guid isPermaLink="true">http://direct.ecency.com/machinelearning/@lesley2958/machine-learning-series-support-vector-machines</guid><category><![CDATA[machinelearning]]></category><dc:creator><![CDATA[lesley2958]]></dc:creator><pubDate>Sun, 13 Aug 2017 01:43:51 GMT</pubDate><enclosure url="https://images.ecency.com/p/mXkfdToSwHy1pbjMQLn1BtkRRRrCGxgE2gX5hPG5SpDpBtcVfRcnAodrszpmxTZAmwPD1d5DHGATKm1JaqZFmR7KBJmXVzqqe7DBfi1Qg?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Introducing R! (Part 1 - Variables & Data Types)]]></title><description><![CDATA[full credit to udemy for providing this photo online here Setup This guide was written in R 3.2.3. R & R Studio Download R and R Studio. Packages Next, to install the R packages, cd into your workspace,]]></description><link>http://direct.ecency.com/r/@lesley2958/introducing-r-part-1-variables-and-data-types</link><guid isPermaLink="true">http://direct.ecency.com/r/@lesley2958/introducing-r-part-1-variables-and-data-types</guid><category><![CDATA[r]]></category><dc:creator><![CDATA[lesley2958]]></dc:creator><pubDate>Fri, 11 Aug 2017 21:45:24 GMT</pubDate><enclosure url="https://images.ecency.com/p/2Qhhdda6Qnbf6Dj2jdaaxHRqfLY15iuw3VvMM4VhftMw6Cv2pquraz5JUMcD4UujzWqM9iFVnXuSRZ4ZyQ7p?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Natural Language Processing with Python & NLTK (Part 2)]]></title><description><![CDATA[image originally from Tertiary Courses Introduction Working off my post from yesterday, I'll continue with Word Taggers, an incredibly important topic in natural language processing. Before you begin this]]></description><link>http://direct.ecency.com/nlp/@lesley2958/natural-language-processing-with-python-and-nltk-part-2</link><guid isPermaLink="true">http://direct.ecency.com/nlp/@lesley2958/natural-language-processing-with-python-and-nltk-part-2</guid><category><![CDATA[nlp]]></category><dc:creator><![CDATA[lesley2958]]></dc:creator><pubDate>Fri, 11 Aug 2017 03:49:48 GMT</pubDate><enclosure url="https://images.ecency.com/p/BM7WWisF8H7NxFR8k8CHYkffFmNQFDf7QXLGRZzWggokEWJMfPAaj7jYRWrcg5ZHsoMvkt4p2NxDAaLUXq8PFk5Ar6gS6rqUjJcgm2HVx3w4qCat2F5GBqeeJACt9cDJt51oRtDiVydsFeh79naAgSyQP5q9XGY4j88tVGJGppNUcrUaBzxs5ruRQQiKMDgA1je8WorTKRtoDjWP42JEksghDZpHfrqzBQffgQ6?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Intro to Data Visualization with Python (Part 1)]]></title><description><![CDATA[1.0 Introduction Data Visualization is an important and exciting aspect of data science. It reveals information we otherwise wouldn't have noticed. It allows us to showcase the work we've done through]]></description><link>http://direct.ecency.com/python/@lesley2958/intro-to-data-visualization-with-python-part-1</link><guid isPermaLink="true">http://direct.ecency.com/python/@lesley2958/intro-to-data-visualization-with-python-part-1</guid><category><![CDATA[python]]></category><dc:creator><![CDATA[lesley2958]]></dc:creator><pubDate>Thu, 10 Aug 2017 17:29:00 GMT</pubDate></item><item><title><![CDATA[Data Preparation with Python & Pandas]]></title><description><![CDATA[0.0 Setup This guide was written in Python 3.6. 0.1 Python and Pip Download Python and Pip. 0.2 Other Let's install the modules we'll need for this tutorial. Open up your terminal and enter the following]]></description><link>http://direct.ecency.com/datascience/@lesley2958/data-preparation-with-python-and-pandas</link><guid isPermaLink="true">http://direct.ecency.com/datascience/@lesley2958/data-preparation-with-python-and-pandas</guid><category><![CDATA[datascience]]></category><dc:creator><![CDATA[lesley2958]]></dc:creator><pubDate>Thu, 10 Aug 2017 14:41:33 GMT</pubDate><enclosure url="https://images.ecency.com/p/62PdCouTvNPD828efm3c7igbxRHz9XKHG4uts2Q2gVZkRJy6DZvXqVbjZPrYANG11WXXEdH2c1aFtYekw3t1ao1bj92Y343ySNML44jqEam7txt?format=match&amp;mode=fit" length="0" type="false"/></item><item><title><![CDATA[Brief Introduction to Natural Language Processing & Regular Expressions (Part 1)]]></title><description><![CDATA[image originally from Tertiary Courses 0.0 Setup This guide was written in Python 3.6. 0.1 Python & Anaconda Download Python and Pip. 0.2 Libraries We'll be working with the re library for regular]]></description><link>http://direct.ecency.com/nlp/@lesley2958/brief-introduction-to-natural-language-processing-part-1</link><guid isPermaLink="true">http://direct.ecency.com/nlp/@lesley2958/brief-introduction-to-natural-language-processing-part-1</guid><category><![CDATA[nlp]]></category><dc:creator><![CDATA[lesley2958]]></dc:creator><pubDate>Thu, 10 Aug 2017 00:29:24 GMT</pubDate><enclosure url="https://images.ecency.com/p/BM7WWisF8H7NxFR8k8CHYkffFmNQFDf7QXLGRZzWggokEWJMfPAaj7jYRWrcg5ZHsoMvkt4p2NxDAaLUXq8PFk5Ar6gS6rqUjJcgm2HVx3w4qCat2F5GBqeeJACt9cDJt51oRtDiVydsFeh79naAgSyQP5q9XGY4j88tVGJGppNUcrUaBzxs5ruRQQiKMDgA1je8WorTKRtoDjWP42JEksghDZpHfrqzBQffgQ6?format=match&amp;mode=fit" length="0" type="false"/></item></channel></rss>